Downhole Measurement Of Formation Characteristics While Drilling

ABSTRACT

Methods and apparatus for acquiring mud gas logging data, comparing the mud gas logging data to second data associated with a sidewall fluid sample measurement, and adjusting calibration data associated with a mud gas logging tool based on the comparison of the mud gas logging data and the second data associated with the sidewall fluid sample measurement.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of and claims priority to U.S. patentapplication Ser. No. 12/993,275, entitled “Downhole Measurement ofFormation Characteristics While Drilling,” filed Nov. 18, 2010, now U.S.Pat. No. 8,714,246, as a national stage of PCT Patent Application No.PCT/US2009/041784, filed Apr. 27, 2009, which claims priority to U.S.Provisional Application No. 61/055,201, filed May 22, 2008, the entiredisclosures of which are hereby incorporated herein by reference.

BACKGROUND OF THE DISCLOSURE

Drilling, completion, and production of hydrocarbon reservoir wellsinvolve drilling boreholes that intersect or traversehydrocarbon-bearing deposits. Typically, drilling rigs at the surfaceare used to drill boreholes to reach the location of subsurface oil orgas deposits and establish fluid communication between the deposits andthe surface via the borehole. Downhole drilling equipment may bedirected or steered to the oil or gas deposits using directionaldrilling techniques.

Evaluations of subterranean formations penetrated by the borehole can beused to identify subsurface formations having characteristics indicativeof good production and/or drainage. To perform such evaluations, thedrilling equipment may be removed from the borehole and a wireline toolcan be deployed into the borehole to sample and/or test one or moreformation fluids at various stations or positions of the wireline tool.Alternatively, the drilling equipment of a drill string may include adownhole tool configured to sample and/or test the fluids of thesurrounding subterranean formation. The sampling may be accomplishedusing formation testing tools that retrieve the formation fluids atdesired borehole positions or stations and/or test the retrieved fluidsin situ. Alternatively, formation fluids may be collected in one or morechambers of the downhole tool which are then brought to the surface andevaluated to determine the properties of the fluids and the condition ofthe subterranean formations, and thereby locate exploitable oil and/orgas deposits.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure is best understood from the following detaileddescription when read with the accompanying figures. It is emphasizedthat, in accordance with the standard practice in the industry, variousfeatures are not drawn to scale. In fact, the dimensions of the variousfeatures may be arbitrarily increased or reduced for clarity ofdiscussion.

FIG. 1A is an elevation view of a wellsite system that may be used toimplement the example methods and apparatus described herein.

FIG. 1B is an elevation view of another wellsite system that may be usedto implement the example methods and apparatus described herein.

FIG. 2 is an example block diagram of a sampling while drilling tool ofthe drill string of FIG. 1B.

FIG. 3A depicts a block diagram of an example apparatus that may be usedto analyze well data to control a drill string to form a well.

FIG. 3B depicts a portion of the example apparatus of FIG. 3A that canbe used to detect and account for fluid compositional variations.

FIGS. 4A and 4B depict a flowchart of an example method that may be usedto implement the example apparatus of FIG. 3 to control the welltrajectory of a well.

FIG. 5 is a flowchart of an example method that may be used to determinewhether to stop drilling operations based on real-time well productionsimulations.

FIG. 6 is a flowchart of an example method that may be used to place awell in a reservoir containing injected fluid.

FIG. 7 is a flowchart of an example method that may be used to adjustwell trajectories to plan a well in a compartmentalized reservoir.

FIG. 8 is a flowchart of an example method that may be used to steer awell trajectory based on asphaltene precipitation onset pressure.

FIG. 9 is a flowchart of an example method that may be used to controlthe trajectory of a well to maintain the well trajectory below a gas-oilcontact in an oil zone.

DETAILED DESCRIPTION

It is to be understood that the following disclosure provides manydifferent embodiments, or examples, for implementing different featuresof various embodiments. Specific examples of components and arrangementsare described below to simplify the present disclosure. These are, ofcourse, merely examples and are not intended to be limiting. Inaddition, the present disclosure may repeat reference numerals and/orletters in the various examples. This repetition is for the purpose ofsimplicity and clarity and does not in itself dictate a relationshipbetween the various embodiments and/or configurations discussed.Moreover, the formation of a first feature over or on a second featurein the description that follows may include embodiments in which thefirst and second features are formed in direct contact, and may alsoinclude embodiments in which additional features may be formedinterposing the first and second features, such that the first andsecond features may not be in direct contact.

The example methods and apparatus described herein may be used todetermine a well trajectory based on real-time or substantiallyreal-time downhole measurements of reservoir fluid properties. Theexample methods and apparatus may be used during exploration andappraisal phases of a reservoir. For example, the example methods andapparatus may be used to steer a drill string to form the welltrajectory so that useful information about the fluid distribution inthe reservoir can be measured. Thus, in some example implementations,the well trajectory may be adjusted to optimize reservoircharacterization.

The example methods and apparatus described herein may also be usedduring a development phase of a reservoir. For example, the examplemethods and apparatus may be used to steer a drill string so that aproducing well engages hydrocarbon accumulations of sufficienteconomical value. Alternatively, the example methods and apparatus maybe used to steer a drill string so that an injection well (e.g., a gasinjection well) engages particular flow units in the reservoir. Thus, insome example implementations, the well trajectory may be adjusted tooptimize the reservoir drainage/production, either directly (as in thecase of a producing well) or indirectly (as in the case of an injectionwell).

The example methods and apparatus described herein may be implemented touse in-situ measurements indicative of formation fluid properties and/ora reservoir fluid property map. A formation fluid property may bedetermined by measuring a property of downhole fluid in or extractedfrom formation rock surrounding the borehole of a well. A reservoirextends beyond the immediate formation rock surrounding the borehole ofa well. A reservoir fluid property map may be determined from themeasured fluid property using various extrapolation techniques furtherdetailed herein.

In some example implementations that use formation fluid properties tocontrol a drill string to form a well trajectory, the example methodsand apparatus described herein may be configured to determine areservoir fluid property map on a portion of a reservoir; convey atleast one fluid property sensor into a reservoir well using, forexample, a drill string; perform in-situ measurements using the sensorindicative of a formation fluid property; compare the in-situmeasurements with the property map; and adjust a well trajectory basedon the comparison. In such example implementations, the example methodsand apparatus may also be configured to determine a reservoir fluidproperty uncertainty map on at least the same portion of the reservoir;determine the uncertainty associated with the in-situ measurementsperformed by the sensor; and compare the in-situ measurementuncertainties with the property map and/or its associated uncertaintymap.

In some example implementations that use reservoir fluid properties tocontrol a drill string to form a well trajectory, the example methodsand apparatus described herein may be configured to convey at least onefluid property sensor into a reservoir well using, for example, a drillstring; perform at least one in-situ measurement using the sensorindicative of a reservoir fluid property; determine a reservoir fluidproperty map on a portion of the reservoir based on the in-situmeasurement; and adjust a well trajectory based on the determinedproperty map. In such example implementations, the example methods andapparatus may also be configured to determine a reservoir fluid propertyuncertainty map associated with the at least one measurement and adjusta well trajectory based on the property map and/or the uncertaintyindicated by the property uncertainty map.

In the examples described herein, the formation and/or reservoir fluidproperties may include properties that are related (e.g., first-orderrelated) to the reservoir fluid composition. The fluid properties may beone or more (e.g., in combination) of fluid compositions (e.g., either apartial or a full description composition), constituent isotope ratios,gas-liquid ratios, etc. Fluid composition data may alternatively bedescribed with thermo-physical data such as, for example, fluid bulkdensity, saturation pressures, viscosity, fluid acoustic impedance(i.e., the square root of the product of the fluid compressibility bythe fluid density), and fluid compressibility at a given pressure andtemperature. In addition, fluid composition data may also be representedby raw spectroscopic data such as, for example, a spectrum of massfragments as used in mass spectrometry, a spectrum of optical densities,fluorescence data, refractive index data, nuclear magnetic resonance(NMR) data, and dielectric spectrum data. In some exampleimplementations, fluid properties may additionally or alternatively berepresented or described using parameters or sets of parameters used inequations that describe characteristics of a fluid such as, for example,sets of parameters used in equations of state (EoS) or coefficientsused, for example, as part of neural network methods and/or radial basisfunctions which are fit to entries contained in one or more fluidproperty databases.

Although the example methods and apparatus described herein may be usedto adjust a well trajectory by adjusting the direction, travel, and pathof a well trajectory, adjusting a well trajectory as described hereinmay also include terminating all further planned drilling operations.Such may be the case where in-situ measurements indicate that it wouldnot be productive to continue drilling a particular well in a particularreservoir or at a particular position in the reservoir.

FIG. 1A illustrates a wellsite system in which the example methods andapparatus described herein can be employed. The wellsite can be onshoreor offshore. In this example system, a borehole 11 is formed insubsurface formations by rotary drilling in a manner that is well known.Example implementations of the example methods and apparatus can alsouse directional drilling, as will be described hereinafter.

A drill string 12 is suspended within the borehole 11 and has a bottomhole assembly 1 which includes a drill bit 2 at its lower end. Thesurface system includes platform and derrick assembly 10 positioned overthe borehole 11, the assembly 10 including a rotary table 16, a kelly17, a hook 18, and a rotary swivel 19. The drill string 12 is rotated bythe rotary table 16, energized by means not shown, which engages thekelly 17 at the upper end of the drill string 12. The drill string 12 issuspended from the hook 18, attached to a traveling block (not shown),through the kelly 17 and the rotary swivel 19, which permits rotation ofthe drill string 12 relative to the hook 18. As is well known, a topdrive system could alternatively be used.

In the illustrated example implementation, the surface system furtherincludes drilling fluid or mud 26 stored in a pit 27 formed at the wellsite. A pump 29 delivers the drilling fluid 26 to the interior of thedrill string 12 via a port in the swivel 19, causing the drilling fluidto flow downwardly through the drill string 12 as indicated by thedirectional arrow 8. The drilling fluid exits the drill string 12 viaports in the drill bit 2, and then circulates upwardly through theannulus region between the outside of the drill string 12 and the wallof the borehole, as indicated by the directional arrows 9. In thiswell-known manner, the drilling fluid 26 lubricates the drill bit 2 andcarries formation cuttings up to the surface as it is returned to thepit 27 for recirculation.

The bottom hole assembly 1 of the illustrated example implementationincludes a logging-while-drilling (LWD) module 4, ameasurement-while-drilling (MWD) module 5, a rotary-steerable system andmotor 6 (e.g., a directional drilling subsystem), and the drill bit 2.

The LWD module 4 is housed in a special type of drill collar, as isknown in the art, and can contain one or a plurality of known types oflogging tools. It will also be understood that more than one LWD and/orMWD module can be employed, e.g., as represented at 7. (References,throughout, to a module at the position of 5 can alternatively mean amodule at the position of 7 as well.) The LWD module 4 includescapabilities for measuring, processing, and storing information, as wellas for communicating with the MWD module 5. In the present embodiment,the LWD module 4 includes a fluid property sensor.

The MWD module 5 is also housed in a special type of drill collar, as isknown in the art, and can contain one or more devices for measuringcharacteristics of the drill string and drill bit. The MWD module 5further includes an apparatus (not shown) for generating electricalpower to the downhole system. This may typically include a mud turbinegenerator powered by the flow of the drilling fluid, it being understoodthat other power and/or battery systems may be employed. In the presentembodiment, the MWD module 5 includes one or more of the following typesof measuring devices: a weight-on-bit measuring device, a torquemeasuring device, a vibration measuring device, a shock measuringdevice, a stick slip measuring device, a direction measuring device,and/or an inclination measuring device. The MWD module 5 furtherincludes capabilities for communicating with surface equipment.

A use of the example methods and apparatus described herein is inconjunction with controlled steering or “directional drilling” using therotary-steerable subsystem 6. Directional drilling is the intentionaldeviation of the wellbore from the path it would naturally take. Inother words, directional drilling is the steering of the drill string sothat it travels in a desired direction. Directional drilling comprisesgeometrical steering, in which the drill bit is typically steered alonga pre-determined path in an Earth formation, and geological steering, inwhich the drill bit is typically steered relative to geological featuresof the Earth formation. Directional drilling is, for example,advantageous in offshore drilling because it enables many wells to bedrilled from a single platform. Directional drilling also enableshorizontal drilling through a reservoir. Horizontal drilling enables alonger length of the wellbore to traverse the reservoir, which increasesthe production rate from the well. A directional drilling system mayalso be used in vertical drilling operations as well. Often the drillbit 2 will veer off of a planned drilling trajectory because of theunpredictable nature of the formations being penetrated or the varyingforces that the drill bit 2 experiences. When such a deviation occurs, adirectional drilling system (e.g., the rotary-steerable subsystem 6) maybe used to put the drill bit 2 back on course.

A known method of directional drilling includes the use of a rotarysteerable system (“RSS”). In an RSS, the drill string 12 is rotated fromthe surface, and downhole devices cause the drill bit 2 to drill in thedesired direction. Rotating the drill string 12 greatly reduces theoccurrences of the drill string 12 getting hung up or stuck duringdrilling. Rotary steerable drilling systems for drilling deviatedboreholes into the earth may be generally classified as either“point-the-bit” systems or “push-the-bit” systems. In the point-the-bitsystem, the axis of rotation of the drill bit 2 is deviated from thelocal axis of the bottom hole assembly 1 in the general direction of thenew hole. The hole is propagated in accordance with the customary threepoint geometry defined by upper and lower stabilizer touch points andthe drill bit 2. The angle of deviation of the drill bit 2 axis coupledwith a finite distance between the drill bit 2 and a lower stabilizerresults in the non-collinear condition required for a curve to begenerated. There are many ways in which this may be achieved including afixed bend at a point in the bottom hole assembly 1 close to the lowerstabilizer or a flexure of the drill bit 2 drive shaft distributedbetween an upper and the lower stabilizer. In its idealized form, thedrill bit 2 is not required to cut sideways because the bit axis iscontinually rotated in the direction of the curved hole. Examples ofpoint-the-bit type rotary steerable systems, and how they operate aredescribed in U.S. Patent Application Publication No. 2001/0052428 andU.S. Pat. Nos. 6,401,842; 6,394,193; 6,364,034; 6,244,361; 6,158,529;6,092,610; and 5,113,953, all of which are hereby incorporated herein byreference in their entireties.

In the push-the-bit rotary steerable system there is usually nospecially identified mechanism to deviate the bit axis from the localbottom hole assembly axis; instead, the requisite non-collinearcondition is achieved by causing either or both of an upper or a lowerstabilizer(s) to apply an eccentric force or displacement in a directionthat is preferentially orientated with respect to the direction of holepropagation. Again, there are many ways in which this may be achieved,including non-rotating (with respect to the hole) eccentric stabilizers(displacement based approaches) and eccentric actuators that apply forceto the drill bit in the desired steering direction. Again, steering isachieved by creating non co-linearity between the drill bit 2 and atleast two other touch points. In some instances, the drill bit 2 isrequired to cut side ways to generate a curved hole. Examples ofpush-the-bit type rotary steerable systems, and how they operate aredescribed in U.S. Pat. Nos. 5,265,682; 5,553,678; 5,803,185; 6,089,332;5,695,015; 5,685,379; 5,706,905; 5,553,679; 5,673,763; 5,520,255;5,603,385; 5,582,259; 5,778,992; 5,971,085, all of which are herebyincorporated herein by reference in their entireties.

FIG. 1B is an elevational view of another wellsite system that may beused to implement the example methods and apparatus described herein. Inthe illustrated example, a platform and derrick assembly 100 arepositioned over a well 102 (e.g., a wellbore or borehole) penetrating asubsurface formation F in a reservoir R. Although the platform andderrick assembly 100 are shown as a land-based rig, the example methodsand apparatus described herein are not limited for use with land-basedrigs. A drill string 104 is suspended within the well 102 and includes adrill bit 106 at its lower end. The drill string 104 is rotated by arotary table 108, energized by means not shown, which engages a kelly110 at the upper end of the drill string 104. The drill string 104 issuspended from a hook 112, attached to a traveling block (not shown),through the kelly 110 and a rotary swivel 114, which permits rotation ofthe drill string 104 relative to the hook 112. In the illustratedexample, the well 102 is formed using directional drilling.

The drill string 104 further includes a bottom hole assembly (BHA) 116coupled to the drill bit 106. The BHA 116 includes a directionaldrilling subassembly 118 to adjust the drilling direction of the drillbit 106 based on control signals received from, for example, a surfacelogging and control system 120. The BHA 116 includes capabilities formeasuring, processing, and storing information, as well as communicatingwith surface equipment. In the illustrated example, the BHA 116includes, among other things, a telemetry and measurement while drilling(MWD) tool 124 (i.e., a survey tool). The MWD tool 124 is configured tosend direction and inclination data to the surface and track the actualwell trajectory of the well 102. The MWD tool 124 is also used toperform two-way telemetry between the surface system 120 and downholecomponents of the BHA 116. For example, the MWD tool 124 can be used toreceive commands from the surface system 120 related to collecting fluidsamples from the well 102 and/or measuring the fluid samples.

In the illustrated example, the BHA 116 is provided with a logging whiledrilling (LWD) tool 126 (i.e., a formation evaluation tool). Althoughone LWD tool 126 is shown, in other example implementations, the BHA 116can be provided with any number of LWD tools. The LWD tool 126 is usedto obtain formation evaluation logs of the well 102 and improve thepetrophysical knowledge of the reservoir R while the well 102 is beingdrilled. The LWD tool 126 and any other LWD tool provided to the BHA 116may be any combination of, for example, a Nuclear Magnetic Resonance(NMR) tool (e.g., the proVISION™ nuclear magnetic resonance whiledrilling tool provided by Schlumberger Technology Corporation), anuclear spectroscopy tool for obtaining lithology and porosityinformation (e.g., the EcoScope™ formation evaluation tool provided bySchlumberger Technology Corporation), a sonic tool (e.g., thesonicVISION™ sonic while drilling tool provided by SchlumbergerTechnology Corporation), a seismic tool (e.g., the seismicVISION™seismic while drilling tool provided by Schlumberger TechnologyCorporation), an acoustic imaging tool, and/or a resistivity imagingtool (e.g., the geoVISION™ resistivity imaging tool and the PeriScope15™ deep-reading resistivity tool both provided by SchlumbergerTechnology Corporation).

To communicate measurement information associated with the formation Fsurrounding the well 102 and the reservoir R to the surface system 120and to receive direction drilling control signals, the bottom holeassembly 116 is provided with a telemetry system 128 that may include,preferably but not necessarily, wired pipes (not shown). A telemetrysystem that may be used to implement the example telemetry system 128 isdescribed in detail in U.S. Patent Application Publ. No. 2007/0029112,which is hereby incorporated herein by reference in its entirety. Forexample, a wireless data transceiver 150 can be coupled to the drillstring 104 as shown in FIG. 1B to exchange data between the surfacelogging control system 120 and the BHA 116. However, other telemetrysystems, such as two ways mud pulse telemetry systems, may alternativelyor additionally be used.

In the illustrated example, the BHA 116 includes a downhole mud gaslogging tool 138. The downhole mud gas logging tool 138 has an inlet 140for receiving fluids from the annulus 136. A portion of the fluidsreceived in the downhole mud gas logging tool 138 via the inlet 140includes formation fluid that has been released into the drilling mud asthe formation rock was crushed during drilling. The mud gas logging tool138 is capable of separating volatiles (e.g., hydrocarbons of lowmolecular weight) from the received fluids and in the process generatinggas using, for example, a volume expansion and/or heating process. Inthe illustrated example, the downhole mud gas logging tool 138 isprovided with a gas sensor 141 to measure the composition of theseparated gases. The composition of the separated gases may be analyzedusing any suitable composition analysis device including, for example, amass spectrometer or a gas chromatographer. In addition, downhole mudgas logging preferably distinguishes between “background” concentrationof hydrocarbon in the mud and “incoming” concentration originating fromthe rock being drilled by periodically measuring and accounting for“background” concentration of hydrocarbon in the mud.

Although many types of hydrocarbons and hydrocarbon structures exist ina reservoir, mud gas logging may only measure a subset of data (e.g.,data indicative of the most volatile components contained in theformation fluid) that can otherwise be acquired using other techniquessuch as, for example, sidewall sampling. Indeed, mud gas logging looksonly at a subset of the hydrocarbons and gases usually encountered inEarth formations (e.g., volatile hydrocarbons, carbon dioxide, hydrogensulphide, nitrogen, etc.) and typically excludes those components thatare trapped in the drill cuttings or are present in the drilling fluid26 but are not easily volatilized (e.g., those components which havemolecular weights at least as large as those of the components ofsynthetic oil-based muds). However, in contrast to sidewall samplingwhich involves halting drilling operations at least momentarily, mud gaslogging involves nearly continuous data acquisition along a well as thewell is being drilled without needing to stop the drill string. In thisway, the mud gas logging data can be used to determine partial butalmost continuous representations of a reservoir fluid while a well isbeing drilled. Further, based on the hydrocarbon concentrationmeasurements (e.g., a ratio of concentration of hydrocarbon types), mudgas logging can be used to determine changes in the type of formationfluids that are expected to be found as soon as a new formation is beingdrilled.

To acquire relatively quantitative mud gas logging data, the mud gaslogging tool 138 is operated in connection with calibration data. Themud gas logging calibration data is generated based on knowncharacteristics or fluid properties of a well. In the illustratedexamples described herein, the mud gas logging calibration data isdetermined, at least in part, based on sidewall sampling data (e.g.,sidewall sample measurements acquired by the sampling while drillingtool 142 described below). As discussed below in connection with theexample process of FIGS. 4A and 4B, the mud gas logging calibration datacan be checked against actual fluid sample measurements acquired usingsidewall sample measurements to determine whether the mud gas loggingcalibration should be adjusted. Hydrocarbon measurements acquired usinga sampling while drilling tool represents snapshots of the fluid in theformation F from different locations. The hydrocarbon measurements arethen used to determine what type of fluid is expected to be present inthe formation. The sidewall sampling measurements then confirm whetherthe fluid type estimations made using the hydrocarbon data provided bythe mud gas logging tool 138 are quantitatively correct or within anaccuracy threshold. If so, the mud gas logging data is deemed to becorrect (or does not require adjustment). Otherwise, the mud gas loggingcalibration data is adjusted to enable the mud gas logging tool 138 togenerate mud gas logging data that is in agreement with the sidewallfluid sample measurements.

A downhole mud gas logging tool that may be used to implement the mudgas logging tool 138 is describe in U.S. Pat. No. 7,458,257, which ishereby incorporated herein by reference in its entirety. In some exampleimplementations, a surface mud gas logging unit may be used in additionto or instead of the downhole mud gas logging tool 138.

In the illustrated example, the bottom hole assembly 116 includes asampling while drilling tool 142. The sampling while drilling tool 142includes a probe 144 to engage a surface of the well 102 to draw fluidsfrom the reservoir R. In other example implementations, straddle packers(not shown) can additionally or alternatively be used to engage andisolate a portion of the surface of the well 102 to draw fluids from thereservoir R.

To determine sampling locations in the formation F, the sampling whiledrilling tool 142 may be operated in connection with a continuousrepresentation of a reservoir fluid along the well trajectory. In someexample implementations, the continuous representations of a reservoirfluid along the well trajectory may be provided by data generated by themud gas logging tool 142. For example, as described earlier, the mud gaslogging tool 142 is capable of providing almost continuousrepresentations of a reservoir fluid while a well is being drilled.Thus, based on a ratio of concentrations of hydrocarbon types measuredby the mud gas logging tool 142, changes in the type of formation fluidsthat are expected to be found can be identified as soon as a newformation is being drilled. The location of such a change may be used toset the sampling tool probe in the suspected new formation. The samplingtool may then draw and analyze formation fluid from the new formationand provide a more complete description of the fluid in that formation.

An example detailed block diagram of the sampling while drilling tool142 is shown in FIG. 2. In the illustrated example of FIG. 2, thesampling while drilling tool 142 is provided with a pump 202 that drawsfluids from the formation F into the tool 142. The pump 202 can becontrolled to withdraw sufficient fluid from the reservoir R so thatcontamination-free reservoir fluid properties can be estimated. That is,during an initial pumping phase, the pump 202 may draw a mixture offormation fluid and the drilling fluid 26 that has invaded the formationF (see filtrate invaded zone 182 in FIG. 1B), which is a contaminant inthe formation fluid. After some time, the fluid drawn by the pump 202has a reduced fraction of contaminants (e.g., invaded drilling fluid 26into the formation F), and measurements on pristine formation fluid canbe performed. In some example implementations in which contaminantsremain in the drawn formation fluid, computational filtering processescan be performed on the fluid sample measurement data to determine fluidproperties of otherwise pristine fluid samples based on the contaminatedsamples. For example, to determine fluid optical density, a convexcombination of optical densities from different fluid samples can beused to determine the fluid optical density of a pristine sample. Todetermine viscosity, a mixing rule such as, for example, a refinery(e.g., quarter power) formula or the Grundbarg-Nissan mixing rule can beapplied to the measured fluid data. To determine fluid composition, asubtraction or skimming method can be used in combination with anequation of state to determine the fluid composition of a pristinesample. In the illustrated examples described herein, these types ofcorrections for contaminated fluid samples are performed in real timewhen well trajectory adjustments are determined in real time.

The sampling while drilling tool 142 also includes one or more fluidsensors to measure the reservoir fluid drawn into the tool 142. In theillustrated example, the sampling while drilling tool 142 is providedwith a spectrometer 204. The spectrometer 204 may be implemented using,for example, a light absorption/fluorescence spectrometer, a NMRspectrometer, or a mass spectrometer. In other example implementations,the sampling while drilling tool 142 may be provided with a gaschromatographer (e.g., to perform one-dimensional or two-dimensional gaschromatography measurements) in addition to or instead of thespectrometer 204. In the illustrated example, the sampling whiledrilling tool 142 is also provided with one or more sensors 205 tomeasure pressure/temperature, density/viscosity, and/or any other fluidproperties. The sampling while drilling tool 142 may optionally includeone or more fluid store(s) 206 connected to a tool fluid bus 230, eachstore including one or more fluid sample chambers in which reservoirfluid recovered during sampling operations can be stored and brought tothe surface for further analysis and/or confirmation of downholeanalyses.

To store, analyze, process, and/or compress test and measurement data(or any other data acquired by the sampling while drilling tool 142),the sampling while drilling tool 142 is provided with an electronicssystem 208. In the illustrated example, the electronics system 208includes a controller 210 (e.g., a CPU and random access memory) tocontrol operations of the sampling while drilling tool 142 and implementmeasurement routines (e.g., to control the spectrometer 204, etc.). Tostore machine accessible instructions that, when executed by thecontroller 210, cause the controller 210 to implement measurementprocesses or any other processes, the electronics system 208 is providedwith an electronic programmable read only memory (EPROM) 212. In theillustrated example, the controller 210 is configured to receive digitaldata from one or more sensors (e.g., the spectrometer 204 and thesensors 205) provided in the sampling while drilling tool 142.

To analyze measurement data, the sampling while drilling tool 142 isprovided with a data processor 214. In the illustrated example, the dataprocessor 214 is configured to determine fluid properties (e.g., fluidcomposition, GOR, saturation pressures, formation mobility, fluid color,asphaltene or wax concentration levels, pressure, temperature, density,viscosity, compressibility, EoS parameters, thermal and chemicalproperties, etc. . . . ) of formation fluid samples based on themeasurement data collected by the spectrometer 204 and/or the one ormore sensors 205. To store measurement data, analysis data, or any otherkind of data, acquired, collected, and/or generated by the samplingwhile drilling tool 142 using, for example, the spectrometer 204, thecontroller 210, and/or the data processor 214, the electronics system208 is provided with a flash memory 216. To communicate information whenthe sampling while drilling tool 142 is downhole, the electronics system208 is provided with a modem 218 that is communicatively coupled to anelectrical tool bus 220 communicatively coupled to the surface loggingand control system 120 (FIG. 1B). In the illustrated example, the modem218 enables the surface logging and control system 120 to retrievemeasurement and/or analysis data stored in the flash memory 216.

In example implementations in which the BHA 116 uses mud-pulsetelemetry, the flash memory 216 preferably, but not necessarily,includes sufficient memory capacity to store all or essential segmentsof sensor measurement data and interpreted or analysis results computedby the sampling while drilling tool 142. In addition, the data processor214 preferably, but not necessarily, has sufficient processing power andthe appropriate algorithms or data analysis routines to generate andstore useable information based on the sensor measurement data. Forexample, the data processor 214 can be configured to process the sensormeasurement data to generate, for example, fluid composition and thefluid constituent uncertainties, which may be compressed and relayed tothe surface system 120 so that real-time decisions can be made todetermine a well trajectory of the well 102 (FIG. 1B). In exampleimplementations in which relatively high-bandwidth communications (e.g.,wired communications via the electrical tool bus 220 of the wired drillstring 104 (FIG. 1B)) are available, the modem 218 can communicate thesensor measurement data to the surface system 120, and the surfacesystem 120 can process and analyze the sensor measurement data.

Although the components of FIG. 2 are shown and described above as beingcommunicatively coupled and arranged in a particular configuration, thecomponents of the sampling while drilling tool 142 can becommunicatively coupled and/or arranged differently than depicted inFIG. 2 without departing from the scope of the present disclosure. Forexample, each of the processor 214 and the controller 210 (and/orprocessors in the surface logging and control system 120 and thecomputer 146 of FIG. 1B) may be any suitable processor, processing unit,microprocessor, and/or controller. The electronics system 208 may be amulti-processor system (and/or multi-controller system) and, thus, mayinclude one or more additional processors (and/or one or more additionalcontrollers) that are identical or similar to the processor 214 (and/orcontroller 210). In addition, the example methods, apparatus, andsystems described herein are not limited to a particular conveyance typebut, instead, may be implemented in connection with different conveyancetypes including, for example, coiled tubing, wireline retrievable,wired-drill-pipe, and/or other conveyance means known in the industry.

Returning to FIG. 1B, although the example BHA 116 is shown as havingthe mud gas logging tool 138 and the sampling while drilling tool 142,in some example implementations, the BHA 116 may be provided with themud gas logging tool 138 but not the sampling while drilling tool 142 ormay be provided with the sampling while drilling tool 142 but not themud gas logging tool 138.

As shown in FIG. 1B, the surface logging and control system 120 iscommunicatively coupled to a computer 146 including a terminaldisplay/input console 148 to enable an operator to monitor and interactwith drilling operation associated with the drill string 104. While thecomputer 146 and the terminal display/input console 148 are depicted asbeing located on the platform and derrick assembly 100, they can beremotely located from the platform and derrick assembly 100 and maycommunicate with the drill string 104 via any communication link knownin the art.

FIG. 3A depicts a block diagram of an example apparatus 300 that may beused to analyze well data to control a drill string (e.g., the drillstring 104 of FIG. 1B) to form a well (e.g., the well 102 of FIG. 1B).In particular, the example apparatus 300 is configured to receivemeasurement and/or analysis data from the BHA 116 of FIG. 1B, analyzethe received data, and control a well trajectory of the well 102 bycontrolling the direction of drilling of the BHA 116. In some exampleimplementations, the example apparatus 300 can be used to adjust thewell trajectory to optimize characterization of the reservoir R (FIG.1B). The example apparatus 300 can additionally or alternatively be usedto adjust the well trajectory to optimize the drainage/production of thereservoir R.

The example apparatus 300 may be implemented in the BHA 116, the surfacelogging and control system 120, the surface computer 146, or in anycombination thereof using any desired combination of hardware, firmware,and/or software. For example, one or more integrated circuits, discretesemiconductor components, or passive electronic components may be used.Additionally or alternatively, some or all of the blocks of the exampleapparatus 300, or parts thereof, may be implemented using instructions,code, and/or other software and/or firmware, etc. stored on a machineaccessible medium that, when executed by, for example, a processorsystem (e.g., the example surface logging and control system 120 (FIG.1B), the computer 146 (FIG. 1B), and/or the example electronics system208 of FIG. 2), perform the operations represented in the flow diagramsof FIGS. 4A, 4B, and 5-9. Although the example apparatus 300 isdescribed as having one of each block described below, the exampleapparatus 300 may be provided with two or more of any block describedbelow. In addition, some blocks may be disabled, omitted, or combinedwith other blocks.

Turning to FIG. 3A in detail, the example apparatus 300 includes areservoir geological model database 302 to store a reservoir geologicalmodel. The example apparatus 300 also includes a formation evaluationlogs database 304 to store formation evaluation logs corresponding towells previously drilled in the reservoir R and/or to a well (e.g., thewell 102) currently being drilled. To store well trajectories(corresponding to previous wells and the current well), the exampleapparatus 300 is provided with a well trajectory database 306. Theexample apparatus 300 is also provided with a fluid analysis reportdatabase 308 to store fluid analysis reports corresponding to laboratoryanalyses of fluid samples collected in previous wells. The fluidanalysis report database 308 also stores in-situ fluid analysis datacollected in previous wells and the current well. In addition, the fluidanalysis report database 308 may be used to store one or more sensorcalibration(s) (e.g., mud gas logging calibration data).

Reservoir geological model data stored in the reservoir geological modeldatabase 302 describes the locations of sedimentary layers, faults, etc.in the reservoir R (FIG. 1B). The geological model can be generatedusing one or more seismic, electro-magnetic, gravity, or other surveysof the reservoir R, for example, prior to drilling a well (e.g., thewell 102 of FIG. 1B). Preferably, but not necessarily, the reservoirgeological model database 302 also stores information relating todepositional sequences and reservoir structural information obtainedfrom well image data such as, for example, gamma ray image data, densityimage data, and/or resistivity image data.

In some example implementations, formation evaluation logs of one wellcan include measurement data acquired in neighboring or offset wells.Formation evaluation log data stored in the formation evaluation logsdatabase 304 can be obtained while drilling (e.g., using the drillstring 104 of FIG. 1B) or after drilling (e.g., using a wireline tool)to determine the physical and chemical properties (e.g., petrophysicalcharacteristics) of formations to better model subsurface fluidreservoirs. In the illustrated example, the formation evaluation logsinclude one or more of natural gamma ray data, resistivity data,porosity data, and density data. The data stored in the formationevaluation log database is preferably, but not necessarily, collectedusing tools which have at least the capabilities of tools referred to as“triple combo” tools that include, for example, a resistivity tool, aneutron porosity tool, and a nuclear density tool.

The formation evaluation logs may additionally or alternatively includespectroscopy data (e.g., nuclear spectroscopy data or NMR spectroscopydata). In the illustrated example, the formation evaluation logspreferably, but not necessarily, include formation pressure/temperaturedata points acquired in one or more offset wells formed in the reservoirR (FIG. 1B). If pressure data (from, for example, neighboring wells) isnot available prior to drilling the current well (e.g., the well 102 ofFIG. 1B), pressure data may be acquired while drilling the current wellusing, for example, the sampling while drilling tool 142 (FIGS. 1B-3B).The formation evaluation logs may also store drilling events indicativeof, for example, a mud loss, a mud weight, a weight on bit, a rate ofpenetration, etc.

Fluid analysis reports stored in the fluid analysis report database 308include data indicative of fluid compositions and thermo physicalproperties (e.g., temperature, pressure, volume, compressibility,density, viscosity, formation volume factor, gas-oil ratio, API gravity,phase envelope, thermal capacity, etc.) of fluids drawn from thereservoir R. The fluid analysis data can be used to determine how fluidproperties vary along different depths of a formation and differentportions of a reservoir. Fluid composition can be measured in-situ or ina laboratory environment. In-situ fluid analysis (i.e., downhole fluidanalysis) data can include data in the fluid analysis reports indicativeof concentration levels of methane C1, ethane C2, CO2, and water H2O. Inaddition, the in-situ fluid analysis data can include concentrationlevels of fluid components such as, for example, the lumped group ofpropane, butane, and pentane C3-5 and the lumped group of hydrocarbonswith 6 or more carbons in their molecules C6+. Gas-oil ratios ofhydrocarbons can be derived from the fluid composition data. Inaddition, in-situ fluid analysis data can also include formation fluidpressure data, and fluid color related to, for example, concentrationlevels of asphaltene. In-situ fluid analysis data may also includedensity and viscosity of the sampled fluid.

In a laboratory environment (e.g., at the surface) fluid composition canbe analyzed up to hydrocarbon chains having 45 carbon atoms (C45), andsometimes longer chains. Other data in the fluid analysis reports thatcan be determined in a laboratory environment include gas-oil ratio(GOR) data, saturate aromatic resin asphaltene (SARA) analysis data, andflow assurance parameters such as, for example, asphaltene onsetpressure, wax appearance/precipitation temperature (e.g., cloud point),and phase transition boundaries. Particular types of laboratories suchas, for example, geochemistry laboratories can be used to performrelatively more specialized analyses including, for example, analysis ofheavy metals, sulfurs, carbon isotopes, and crude oil fingerprinting.These specialized analyses can be used to investigate the origin of oilin a fluid and identify areas of reservoir compartmentalization (forexample, geological segmentation of reservoirs into isolatedcompartments).

In the illustrated example, the example apparatus 300 is provided with apetrophysics simulator 310 to determine distributions of porosity,lithology and fluid content along the well 102 corresponding to theformation evaluation log data. In the illustrated example, thepetrophysics simulator 310 receives data from the formation evaluationlogs database 304 to determine or simulate porosity, lithology, andfluid content data corresponding to the reservoir R based on the loginformation of the formation F and stored in the formation evaluationlogs database 304. In some example implementations, the fluid contentdata determined by the petrophysics simulator 310 represents a “blackoil model” that includes coarse data indicative of proportions of water,oil and free gas without distinguishing between, for example, the type(e.g., the composition) of the oil. In the illustrated example, theDecisonXpress™ petrophysical evaluation system developed and sold bySchlumberger Technology Corporation can be used to implement thepetrophysics simulator 310.

To refine the description of the reservoir fluid determined by thepetrophysics simulator 310 (e.g., C1, C2, C3-C5, C6+, and/or asphalteneconcentrations) and, in particular, to determine the spatialdistribution of the components of hydrocarbons, or other fluids, alongthe well, the example apparatus 300 is provided with a fluid simulator312. In the illustrated example, the fluid analysis report data from thefluid analysis report database 308 is communicated to the fluidsimulator 312. In addition, the parameters used in the fluid simulator312 to parameterize the variation of fluid composition within theindividual flow units or segments of the well, may be used together withtheir associated uncertainties to perform comparisons between fluids indifferent flow units to determine how fluid properties or fluidcharacteristics change between the different flow units.

In some example implementations, the fluid simulator 312 can beconfigured to determine an equation of state (EoS) from data stored inthe fluid analysis reports. An EoS simulator determines an equation ofstate (e.g., the Peng-Robinson EoS) that relates oil composition,temperature, volume and pressure to represent the thermodynamic behaviorof each fluid sample. The EoS can be used to compute fluid compositionvariations (e.g., concentrations of methane C1, the lumped group ofhydrocarbons with 6 or more carbons C6+, asphaltene, etc.) in the flowunit, segment, or interval to which the fluid sample belongs. Typically,a flow unit is a rock or material volume in which the fluid may freelymigrate. By segmenting each well (e.g., the well 102) according to theflow units through which it passes and determining at least one equationof state in each flow unit, the fluid simulator 312 can be used todetermine a hydrocarbon composition distribution along the entire well.In the illustrated example, the PVT Pro™ EoS simulation tool developedand sold by Schlumberger Technology Corporation can be used to implementthe fluid EoS simulator of the fluid simulator 312, or the PVTi™ EoStool developed and sold by Schlumberger Technology Corporation can beused to implement the fluid simulator 312.

In yet other example implementations, one or more properties measuredalong the well 102 using in-situ fluid analysis sensors are stored in afluid analysis database 308 and are communicated to the fluid simulator312. The fluid simulator 312 determines (e.g., by surface fitting, byemploying neural network techniques or other well-known methods) a trendin the measured property(ies) and extrapolates this trend along eachflow unit or segment of a well.

In the illustrated example, the example apparatus 300 is provided with areservoir simulator 314 which generates a fluid composition distributionacross an entire reservoir. Specifically, when fluid composition data isobtained (e.g., using the petrophysics simulator 310 and/or the fluidsimulator 312) along a plurality of wells in a reservoir, the reservoirsimulator 314 can arrange the fluid composition data to generate a fluidcomposition distribution for that reservoir. In the illustrated example,the reservoir simulator 314 is configured to use the features of thegeological model stored in the reservoir geological model database 302to populate the entire simulated reservoir in an empirical manner. Thatis, as the geological model data improves or more geological model datais acquired using, for example, fluid sample measurements or other typesof measurements, the reservoir simulator 314 can update the fluidcomposition distribution or fluid map of the reservoir R.

The reservoir simulator 314 may be a finite difference, a finiteelement, a finite volume or a streamline simulator that solves theequations governing the distribution of fluids and their fluidcomponents at the scale of the reservoir R under constraints imposed bythe fluid compositions measured along each well. In the illustratedexample, the grid blocks of the reservoir simulator 314 should not betoo coarse, but should instead be fine enough to capture the level ofvariation suitable for controlling drilling operations. The parameters(e.g., temperature gradient, capillary pressure curves, etc.) associatedwith equations governing the fluid distribution can be determined fromprior knowledge (e.g., prior measurement data and/or analysis data ofthe reservoir R stored in, for example, the formation evaluation logsdatabase 304, including, but not limited to, nuclear magnetic resonanceand/or core data acquired in offset wells). Additionally, oralternatively, the petrophysics simulator 310 can determine the watersaturation profile across a water-oil contact in the reservoir R fromthe formation evaluations logs database 304 and determine capillarypressure curves based on the water saturation profile data and sandfacepressure measurements acquired with a sampling while drilling tool 142.In the illustrated example, the capillary pressure curves can in turn beused by the reservoir simulator 314 to determine water saturation levelsaway from the wellbore. In some example implementations, the ECLIPSE™reservoir simulator tool developed and sold by Schlumberger TechnologyCorporation can be used to implement the reservoir simulator 314.

In some example implementations, an EoS determined by the fluidsimulator 312 may also be used to populate the fluid compositiondistribution over a simulated reservoir where the fluid is suspected tobe in thermodynamic equilibrium and where the crude oil may be treatedas a true molecular solution.

In other example implementations, stochastic processes conditioned tomeasurements made at key or select wells may be used to simulate areservoir and populate the composition distribution over the simulatedreservoir.

In some example implementations, models of non-equilibrium distributionsof hydrocarbons can be used to analyze actual reservoir fluids andpopulate the composition distribution over the simulated reservoir. Nonequilibrium distributions occur when reservoir fluids deviate fromequilibrium, which can happen for different reasons. For example,reservoir fluids can deviate from equilibrium due to different factorsincluding biodegradation, thermal gradients, current reservoir charging,charge history coupled with slow mixing kinetics, water/gas washing,leaky seals, and/or miscible floods. Typically, these factors can bemodeled using an adjusted static model. In some instances, if one of thefactors dominates the disequilibrium, that factor can be modeled with asimple parameter or set of parameters. For example, an empirical modelcan be used to find a linearly increasing contribution of biodegradationincreasing towards an oil-water contact.

In other example implementations, Archimedes buoyancy in Boltzmannequation shown in equation 1 below can be used to populate theasphaltene concentration level over a reservoir and/or to determine theexpected optical density (OD) in the visible range resulting from theasphaltene concentration level. For example, measurements may beconducted to detect asphaltene concentration levels in fluid samples anddevelop fluid models based on those asphaltene concentration levels.Asphaltenes are often present in crude oil as a nanocolloidalsuspension, especially in highly under-saturated black oils. Asphalteneconcentration is measurable using optical fluid analysis and, thus, onecan determine if a black oil encountered is the expected black oil. Thatis, in drilling a new well, one can first predict and then performmeasurements in real time to determine whether the black oil encounteredin any flow unit or segment has the asphaltene content expected based ona fluid model of the reservoir previously developed using, for example,equation 1 below.

$\begin{matrix}{\frac{{OD}(h)}{{OD}(0)} = {\exp \left\{ {- \frac{V\; \Delta \; \rho \; g\; h}{k\; T}} \right\}}} & {{Equation}\mspace{14mu} 1}\end{matrix}$

In equation 1 above, OD(h) is the optical density or color of the oil ata height (h) induced by the asphaltene content, (V) is the volume of theasphaltene colloidal particle (found to be ˜16 Å for black oils), (Δρ)is the density contrast between asphaltene and the bulk oil, (g) is theEarth's gravitational constant, (k) is the Boltzmann's constant, and (T)is the temperature. For compressible oils, a semi-empirical methodologycould alternatively be employed to describe the asphaltene concentrationin those compressible oils.

In the illustrated example, the example apparatus 300 is provided with areservoir fluid map database 316 to store maps of fluid content (e.g.,oil, water, gas) and the fluid composition maps of at least one of oil,water, or gas for subsequent use to determine well trajectories. Forexample, a reservoir fluid map data stored in the reservoir fluid mapdatabase 316 may be used when simulating production corresponding to twohypothetical production well trajectories. In such a case, the reservoirfluid map data is used to populate input data for prediction modules 315including a well production simulator 318 and/or a tool responsesimulator 320. In the illustrated examples described herein, thereservoir fluid maps can include data corresponding to portions of basinmodels generated using the reservoir simulator 314. A basin denotes adepression in the Earth's crust in which sediments accumulate. Ifhydrocarbon source rocks or material occur in combination withappropriate depth and duration of burial, then a petroleum system candevelop within the basin. A basin model is a model that may account forthe evolution of hydrocarbons from a source rock and theirtransformation with temperature and time, may model the migration andaccumulation of hydrocarbons within the confines and structural featuresof the basin, and may allow the estimation of the associated uncertaintylevels in the predictions of the reservoir simulator 314 across thegeologic ages. Where reservoir fluid maps include basin simulated data,the reservoir fluid maps would represent the result of the simulatedbasin for the present days near the time frame during which measurementsare acquired to determine well trajectories. A more detailed discussionof how the reservoir simulator 314 simulates basin data is presentedbelow in connection with FIG. 3B.

As shown in FIG. 3A, the example apparatus 300 is provided with the wellproduction simulator 318 to predict a well's production by simulating amultiphase production flow in at least a portion of the reservoirsurrounding a currently drilled well (e.g., the well 102 of FIG. 1B).For example, the well production simulator 318 can utilize other datarelating to relative permeabilities, end point saturations (e.g., boundwater fraction), and capillary pressure curves determined by, forexample, the petrophysics simulator 310. In addition, the wellproduction simulator 318 can utilize formation pressure/temperaturedata, fluid mobility data acquired while sampling, drilling relatedinformation, mud filtrate invasion (see for example invaded zone 182 ofFIG. 1B) data (which may be deduced from open-hole logs), and NMR datafrom the formation evaluation logs database 304. The reservoir simulator314 can use these properties in connection with the geological trendsdescribed by the geological model stored in the reservoir geologicalmodel database 302 to generate a visual three-dimensional volume aroundthe drilled well 102. Thus, the well production simulator 318 can usethe generated three-dimensional volume to predict how much hydrocarboncan be recovered for each hypothetical well trajectory, and the welltrajectory to be formed by the drill string 104 (FIG. 1B) can beselected based on the drainage of the reservoir R it provides. In theillustrated example, the well production simulator 318 can beimplemented using the SWPM™ (Single Well Predictive Modeling) tooldeveloped and sold by Schlumberger Technology Corporation.

Alternatively or additionally, the fluid map data stored in thereservoir fluid map database 316 can be used to predict a reservoirfluid log along the trajectory of a well. In this case, the fluid andgeology map data from the reservoir map database 316 is communicated tothe tool response simulator 320 that is configured to generate visualrepresentations of the formation evaluation log data measured by thelogging while drilling subsystem 126 and stored in the formationevaluation logs database 304 as the well 102 is being drilled. In theexample implementations described herein, vertical well intersectionsare created along the well trajectory paths to create “well curtainsections” used to visualize the position of the well trajectory pathsrelative to seismic sections, faults, formation dips, marker beds,and/or other geologic features or properties of a reservoir. Thus, inthe illustrated example, the tool response simulator 320 can determinepredicted log data along a particular intersection with a welltrajectory using composition information stored in the reservoir fluidmap database 316. The predicted log data represents log data (e.g.,optical spectroscopy absorbances in predetermined wavelength in thevisible, near infrared range in the case of an optical spectrometer,mass spectra in the case of a mass spectrometer, or gas chromatographymeasurements) that would be acquired by fluid sensors (e.g., thespectrometer 204, a gas chromatographer, and/or the sensors 205 of FIG.2) implemented in a drilling system (e.g., the BHA 116 of FIG. 1B) ifcertain well trajectories were to be drilled. In this manner, anoperator can select a particular well trajectory computed by the toolresponse simulator 320 showing predicted log data that the operatorwould like to achieve in actual measurements. Subsequently, duringdrilling operations to form or drill a selected well trajectory, thepredicted log data can be compared to actual measurements collectedusing the downhole mud logging tool 138 of FIG. 1B or to the compositionof the pumped fluid measured using the sampling while drilling tool 142(FIGS. 1B-3B). The surface logging and control system 120 can use theresults of these comparisons to control the directional drillingsubsystem 118 (FIG. 1B) to adjust the trajectory of the well 102. In theillustrated example, the Petrel™ tool developed and sold by SchlumbergerTechnology Corporation can be used to implement the tool responsesimulator 320.

In the illustrated example, the example apparatus 300 is provided withor is coupled to the display/input interface unit 148 of FIGS. 1B, 3A,and 3B. The display/input interface unit 148 can be used to display toan operator the results of various operations based on the fluid mapdata, in conjunction with measurement data acquired by the BHA 116 andinterpreted by the surface system 120. Based on the displayedinformation, the operator may elect to select a particular welltrajectory via the display/input interface unit 148. The exampleapparatus 300 is provided with a trajectory adjustment interface 324 tostore the user-selected well trajectory in the well trajectory database306. In addition, the trajectory adjustment interface 324 can apply theoperator's selection in real time by communicating commands to the BHA116 to achieve the selected trajectory. For example, the trajectoryadjustment interface 324 can communicate commands to the communicationsapparatus 128 of the BHA 116 to control the directional drillingsubsystem 118 (FIGS. 1B and 3A) based on the selected well trajectorystored in the well trajectory database 306.

In the illustrated example, the BHA 116 is coupled to the exampleapparatus 300. In this manner, real-time measurements performed by theLWD tool 126 and/or the sampling while drilling tool 142 and/or the mudgas logging tool 138 can be used to update the formation evaluation logsdatabase 304 and/or the fluid analysis reports database 308. In thismanner, the data in the formation evaluation logs database 304 and/orthe fluid analysis reports database 308 can subsequently be used todetermine new fluid maps as the well is being drilled. In addition,real-time measurements performed by the MWD tool 124 can be used toupdate the current well trajectory data in the well trajectory database306.

FIG. 3B illustrates a portion of the example apparatus 300 of FIG. 3A toshow how the reservoir simulator 314 can, among other things, be used todetect fluid compositional variation in a reservoir. The detectedvariations may in turn be accounted for in the reservoir geologicaldatabase 302 by inferring the occurrence of flow barriers (e.g., flowbarrier 180 of FIG. 1B) or of reservoir charging (typically the historyof an external flux of mass, such as gas or oil or even water in thereservoir). In the illustrated example, the reservoir simulator 314simulates basin data. In some example implementations, the well 102 canbe drilled along the reservoir R while monitoring the reservoir fluidproperties to identify barriers to fluid flow. A barrier can be detectedbased on, for example but not exclusively, the detection of an abruptchange in the fluid pressure, the gas-oil ratio (GOR) or the color ofthe fluid within the reservoir R. Barrier detections can be confirmedusing a vertical interference test or a drill stem test.

In the illustrated example, to detect fluid flows and barriers, thereservoir geological model database 302 stores connectivity model data332 and charging model data 334. In other example implementations, theconnectivity model data 332 and the charging model data 334 can bestored on a different database. The connectivity model data 332describes faults, possible flow passages, flow resistance, etc. in thereservoir R. The charging model data 334 describes the source ofdownhole fluid (e.g., the composition, flow direction, etc.). In someexample implementations, the connectivity model data 332 and thecharging model data 334 may be represented as a function of geologicaltime.

In the illustrated example, the reservoir simulator 314 uses theconnectivity model data 332 and the charging model data 334 to predictthe migration of the downhole fluids from one or more respective sourcerocks into other areas of the reservoir R and the change in the fluidcomposition(s) as a function of geological time. In addition, thereservoir simulator 314 can determine uncertainties for each of itspredictions and store the predictions and their associated uncertaintiescorresponding to particular times (e.g., present time or future times)in the reservoir fluid map 316.

In operation, the data in the reservoir fluid map database 316 may becommunicated to the tool response simulator 320, which uses the data topredict what the sampling while drilling tool 142 would measure ifcertain wellbore trajectories were followed. After following (e.g.,drilling or forming) a particular wellbore trajectory, the samplingwhile drilling tool 142 (or the mud gas logging tool 138, not shown)performs actual formation fluid measurements, and a charging adjustmentinterface 336 and a barrier adjustment interface 338 can compare theactual measurements to the predicted data to determine whether to makeadjustments to the charging model data 334 or the connectivity modeldata 332, respectively. For example, if the actual fluid samplemeasurements indicate inaccuracies in the connectivity model data 332,then the barrier adjustment interface 338 can adjust the connectivitymodel data 332 to better conform to the actual fluid samplemeasurements. By adjusting the connectivity model data 332 and thecharging model data 334 based on actual fluid measurement analyses, thereservoir simulator 314 can determine relatively more accurate reservoirfluid map data for the reservoir fluid map database 316. In this manner,the connectivity model data 332 and/or the charging model data 334 canbe adjusted until the predictions generated by the tool responsesimulator 320 and the actual fluid sample measurements are insubstantial agreement. Thus, the presence of a barrier can be detectedwhen the data predicted by the tool response simulator 320 is not insubstantial agreement with the actual fluid sample measurements.

If the charging adjustment interface 336 and the barrier adjustmentinterface 338 determine that the actual fluid sample measurements are insubstantial agreement (i.e., within the uncertainty of the measurement)with the predicted data generated by the tool response simulator 320,then the confidence about the reservoir fluid map data in the reservoirfluid map database 316 increases and, thus, the uncertainties associatedwith the reservoir fluid map data may be reduced in the reservoir fluidmap database 316. Thus, the presence of a barrier can be confirmed whenthe data predicted by the tool response simulator 320 is in substantialagreement with the actual fluid sample measurements.

FIGS. 4A and 4B depict a flowchart of an example method that may beimplemented with the example apparatus 300 of FIG. 3A to control thewell trajectory of a well (e.g., the well 102 of FIG. 1B). The examplemethod of FIGS. 4A and 4B may be implemented using software and/orhardware. Although the example method is described with reference to theflowchart of FIGS. 4A and 4B, other methods may additionally oralternatively be used. For example, the order of execution of the blocksdepicted in the flowchart of FIGS. 4A and 4B may be changed, and/or someof the blocks described may be rearranged, eliminated, or combined.

Turning to FIG. 4A, initially, the example apparatus 300 collects priordata about the reservoir R in which the well 102 is to be drilled (block402), if available. Prior data may include a seismic cube of thereservoir R, logs of previous wells drilled in the reservoir, laboratoryresults for fluid samples or core samples obtained from the reservoir,etc. In the illustrated example, the example apparatus 300 stores theprior data in the reservoir geological model database 302, the formationevaluation logs database 304, and the fluid analysis report database308. If the prior data about the reservoir R is not available,measurements on a currently drilled well (e.g., the well 102 of FIG. 1B)can be performed to collect data about the reservoir R for the reservoirgeological model database 302, the formation evaluation logs database304, and/or the fluid analysis report database 308.

The reservoir simulator 314 (FIG. 3A) determines an initial reservoirfluid map from the prior data and determines an uncertainty map (block404) of the reservoir R. The uncertainty map is used to indicate theuncertainties in the fluid property predictions in the well 102. Theinitial fluid map may have a high level of uncertainty. However, usingthe example methods and apparatus described herein in a recursive mannerwhile drilling a well enables collecting data to reduce theuncertainties as the well is drilled and, thus, may update the welltrajectory in real time based on updates to the fluid map as theuncertainties are reduced.

The well production simulator 318 or the tool response simulator 320 maybe used by an operator to determine at least one initial well trajectory(block 406) based on, for example, the initial fluid map data determinedat block 404 and stored in the reservoir fluid map database 316. In someexample implementations, an initial well trajectory is designed toenable new fluid measurements to be made to reduce the uncertainty ofthe reservoir fluid map determined at block 404. In other exampleimplementations, the well production simulator 318 is used to determinean initial well trajectory at block 406 that is designed to optimizehydrocarbon recovery from a reservoir. In yet other exampleimplementations, the tool response simulator 320 can determine one ormore well trajectories that are contingent on fluid measurements duringthe drilling of the well 102, and the tool response simulator 320 can beused to select one of the well trajectories at block 406 as the initialwell trajectory to optimize a particular objective (e.g., particularfluid measurement data). The drill string 104 (FIG. 1B) is lowered inthe well 102 (block 408), and drilling is started (block 410).

As described below, measurement data is collected by the BHA 116, andthe measurement data can be used in real time by the example apparatus300 of FIG. 3A to update reports, models, and simulations in the exampleapparatus 300. Measurement data can be collected before drilling, duringdrilling pauses, and/or after drilling the well 102 (e.g., whiletripping out of the well).

In the illustrated example, the downhole mud gas logging tool 138acquires downhole mud gas logging data (block 412). In other exampleimplementations, surface mud gas logging data may be used instead ofdownhole mud gas logging data, but the surface mud gas logging data maynot be accurately indicative of the actual characteristics of thesubsurface reservoir R. Mud gas logging data can be acquired duringdrilling without the need to stop or pause drilling. In the illustratedexample, the mud gas logging data is used to derive information aboutthe formation F being drilled and, more particularly, about the mostvolatile components contained in the formation fluid which are entrainedin the drilling fluid as the formation rock is crushed by the drill bit106. The downhole mud gas logging tool 138 extracts these componentsfrom drilling mud in-situ and, more specifically, from drilling mudhaving formation fluid originating from within the formation F shortlyafter the drill bit 106 passes a given depth. In this manner, thedownhole mud gas logging tool 138 can analyze the flashed gascomposition in, for example, a continuous fashion. After accounting forthe background composition (e.g., the composition of the incomingdrilling fluid 26 (FIG. 1B) flowing from the drill bit 106), the changein the formation fluid composition introduced in the drilling fluid 26by the drilling process may be determined.

In some example implementations, the mud gas logging tool 138 canmonitor one or more molecular concentration(s) (e.g., methaneconcentration, ethane concentration, carbon dioxide concentration,concentration of a fluid injected in the reservoir etc. . . . )extracted from the drilling mud samples after accounting forconcentrations initially present in the drilling fluid 26 leaving thedrill bit 106. In other example implementations, the mud gas loggingtool 138 may also be used to monitor one or more concentration(s) ofisotopes (e.g., the isotopes of carbon, 12C, 13C, etc. . . . )associated with gases extracted from the drilling mud samples afteraccounting for concentrations initially present in the drilling fluid 26leaving the drill bit 106. The monitored concentrations or other valuesderived therefrom are compared to corresponding log data predicted fromthe fluid map by the tool response simulator 320. In some cases, adiscrepancy between measured data and predicted data greater than themeasurement uncertainty may be indicative of compartmentalization thatwas not accounted for in the reservoir fluid model. In other cases, adiscrepancy between measured data and predicted data greater than themeasurement uncertainty may be indicative of the source of the methane,or carbon dioxide that was not accounted for in the reservoir fluidmodel. In yet other cases, a discrepancy between measured data andpredicted data greater than the measurement uncertainty may beindicative of inaccurate composition gradients or inaccurate location offlood fronts in the fluid model.

In addition, the relative concentrations of the fluid constituentsmeasured by the mud gas logging tool 138 may be used to distinguishbetween fluids in the reservoir and/or to indicate, but not necessarilyprove, the origin of the fluids. For example, carbon isotopemeasurements can be used to advantage for identifying the origin andmaturity of hydrocarbons. Less definitively, the commonly used mud-gaslogging wetness and balance ratios, respectively

$\begin{matrix}{{W = {\sum\limits_{n = 2}^{5}{\left\lbrack C_{n} \right\rbrack/{\sum\limits_{n = 1}^{5}\left\lbrack C_{n} \right\rbrack}}}},} & {B = {\sum\limits_{n = 1}^{5}{\left\lbrack C_{n} \right\rbrack/{\sum\limits_{n = 3}^{5}\left\lbrack C_{n} \right\rbrack}}}}\end{matrix},$

can be used to indicate the source of the gas occurring in the reservoirR. Other ratios, such as the Bernard ratio

$\left\lbrack C_{1} \right\rbrack/{\sum\limits_{n = 2}^{3}\left\lbrack C_{n} \right\rbrack}$

when plotted against the carbon isotope difference ratio, or plots of[C₁]/[C₂] versus or versus [C₂]/[C₃] the carbon isotope difference ratiocan also be used as means for distinguishing between fluid origins.

In the illustrated example, the measurements made by the mud gas loggingtool 138 may be used to determine if a sidewall fluid sampling operationshould be performed (block 414). In the illustrated example, the surfacesystem 120 uses the measurement information provided by the mud gaslogging tool 138 and predicted information generated by the toolresponse simulator 320 to determine whether the fluid sampling operationshould be performed. For example, a discrepancy between mud gas loggingdata measured by the mud gas logging tool 138 and predicted mud gaslogging data generated by the tool response simulator 320 may beindicative of a flow barrier (e.g., flow barrier 180 of FIG. 1B) or acharging history improperly accounted for as the reservoir fluid map(stored in the reservoir fluid map database 316) has been determined. Ifsuch a discrepancy exists between the measured and the predicted mud gaslogging data, a surface system 120 may cause the sampling while drillingtool 142 to extract and optionally to store one or more fluid samplesfrom the formation and perform one or more fluid sample measurements.Thus, a sidewall fluid sampling operation may be performed if the mudgas logging data indicates that a significant change in fluidcomposition has occurred. Alternatively, a sidewall sampling operationmay be scheduled at predetermined intervals or check points along thewell trajectory such as, for example, close to expected gas-oil oroil-water contacts or other fluid transitions. In some exampleimplementations, the operation of block 414 could be performed by anoperator (e.g., an operator-performed decision) and the operator couldprovide user input based on the measurements made by the mud gas loggingtool 138. For example, the computer 146 (FIG. 1B) could display the mudgas logging data received from the BHA 116 and the predicted mud gaslogging data generated by the tool response simulator 320 via theterminal display/input console 148 using a display or presentationconfiguration or arrangement that facilitates an operator-performedcomparison of the data.

If a sidewall sampling operation is to be performed (block 414), thesampling while drilling system 142 acquires sidewall sampling data(block 416). For example, the drilling operation of the BHA 116 ismomentarily stopped and the probe 144 of the sampling while drillingtool 142 is extended to engage the formation F. The pump 202 is used tocontrollably draw fluid from the formation F. Fluid extraction continuesuntil an acceptably low level of contamination (e.g., caused by seepageof the drilling fluid 26 into the formation F) in the sampled stream isobtained. One of the sensors 205 in the sampling while drilling tool 142measures formation fluid pressure and temperature, and the spectrometer204 measures fluid spectroscopic data of the fluid sample. A coarsefluid composition of the pristine formation fluid may be derived fromthe spectroscopic data, including partial concentrations such as methaneconcentration C1, ethane concentration C2, lumped concentration ofpropane, butanes and pentanes, C3-5, a lumped concentration ofhydrocarbons having 6 or more carbon atoms in their molecules C6+,carbon dioxide concentration CO2. Also, GOR can be determined from thefluid composition, and asphaltene concentration may be derived from theoptical density in the visible range measured using the spectrometer204. In addition, water cut may be determined from spectroscopic data inthe near infra-red range. Also, connate water acidity (pH), salinity(resistivity) can be determined. Finally, fluid mobility, fluidviscosity, and density may also be provided by analyzing the dataobtained from one of the sensors 205.

The surface logging and control system 120 and/or the downholeelectronics 208 compares the data derived from the measurements acquiredduring the sidewall sampling operation of block 416 with the mud gaslogging data (acquired using the mud gas logging tool 138) (block 417).For example, the surface logging and control system 120 can comparefluid composition data such as fluid component concentrations, or anyother measurement data acquired during the sidewall sampling operationor data derived from the measurement data, such as uncertainty levels.

The surface logging and control system 120 then determines whether itshould adjust a calibration of the mud gas logging tool 138 (block 418).For example, the surface logging and control system 120 can determinethat it should adjust the mud gas logging calibration if the comparisonbetween the sidewall sampling measurement and the mud gas logging dataperformed at block 417 indicates that the mud gas logging data is notsufficiently in agreement with the sidewall sampling measurement withinan acceptable measurement uncertainty. For example, the results of themud gas logging tool 138 can be recalibrated based on the sidewallsampling measurements to provide an updated or relatively more accurateset of continuous fluid property logs along the well trajectory. In someexample implementations, to compare the mud gas logging data to thesidewall sampling measurements, the surface logging and control system120 compares a subset of fluid composition components (e.g., C1-C8)acquired using the mud gas logging tool 138 to the same componentconcentrations measured during the sidewall sampling operation.Alternatively, the surface logging control system 120 can compare ratiosof hydrocarbon concentrations acquired using the mud gas logging tool138 to ratios of the same hydrocarbon concentrations acquired using thesidewall sampling operation.

If the surface logging and control system 120 determines that it shouldadjust the mud gas logging calibration (block 418), the surface loggingand control system 120 adjusts the mud gas logging calibration (block419). In the illustrated example, the surface logging and control system120 can adjust the mud gas logging calibration by updating fluidcomponent ratios used as the calibration data. For example, if thecalibration data includes a methane concentration calibration parameterand the mud gas logging measurement data indicates a methaneconcentration ratio of 60% while the sidewall sampling measurementindicates a methane concentration ratio of 50%, the calibrationparameter corresponding to the methane concentration ratio can beadjusted until the mud gas logging measurement data indicates a methaneconcentration ratio of 50% in agreement with the sidewall samplingmeasurement. Calibration data for other fluid components measured usingthe mud gas logging tool 138 can be adjusted in a similar manner. Thesurface logging and control system 120 can store the mud gas loggingcalibration data in a memory in the mud gas logging tool 138 forsubsequent use by the mud gas logging tool 138.

After the surface logging and control system 120 adjusts the mud gaslogging calibration (block 419) or if the surface logging and controlsystem 120 determines that it should not adjust the mud gas loggingcalibration data (block 418) or if a sidewall sample measurement is notperformed (block 414), the surface logging and control system 120compares at least one of the measured fluid composition data (and itscomposition uncertainty) derived from the measurements acquired by themud gas logging tool 138 at block 412 and the measured fluid compositiondata (and its composition uncertainty) derived from the measurementsacquired during the sidewall sampling operation of block 416 with thepredicted and/or desired (or target) composition data (and itscomposition uncertainty) (block 420). For example, the surface loggingand control system 120 can compare fluid composition data, temperature,pressure, fluid component concentrations, or any other measurement dataacquired or data derived from the measurement data. Measured compositiondata or other properties derived therefrom can be compared to a logpredicted by the tool response simulator 320 (FIG. 3A) based on thereservoir fluid map data in the reservoir fluid map database 316.

In some example implementations, the comparison operation of block 420could be performed by an operator (e.g., an operator-performedcomparison) and the operator could provide user input based on thecomparison (e.g., a decision to update the reservoir fluid map in thereservoir fluid map database 316 based on the comparison, etc.). Forexample, the computer 146 (FIG. 1B) could receive from the BHA 116 themeasured fluid composition data derived from the measurements acquiredby the mud gas logging tool 138 at block 412 and/or from themeasurements acquired during the sidewall sampling operation of block416. The computer 146 could further display the received measured fluidcomposition data and a log predicted from the reservoir fluid map datavia the terminal display/input console 148 using a presentationconfiguration or arrangement that facilitates an operator-performedcomparison of the data.

The surface logging and control system 120 determines whether to updatethe reservoir fluid map in the reservoir fluid map database 316 (block421) (FIG. 4B). For example, the surface logging and control system 120may determine whether to update the reservoir fluid map based on thecomparisons between fluid composition measurements and predictioncomposition data performed at block 420. In the illustrated example, thesurface logging and control system 120 can determine that it shouldupdate the reservoir fluid map when a discrepancy is observed betweenthe sidewall sampling data and the measurement data predicted from thefluid map (e.g., a gas-oil contact is incorrectly located on the fluidmap) and/or the mud gas logging data and the predicted measurement data.Whether discrepancies exist to warrant an update to the reservoir fluidmap may be based on whether differences between the compared dataindicate discrepancies that exceed an acceptable discrepancy threshold.The value or level of the discrepancy threshold may be directly relatedto the amount or magnitude of uncertainty in the measured and/orpredicted composition data such that if the uncertainty is relativelylarge, the discrepancy threshold may be set to be more accepting oflarger differences, whereas if the uncertainty is relatively small, thediscrepancy threshold may be set to be less accepting of largerdifferences. When no discrepancies warranting an update of the fluid mapare detected based on the comparisons, the surface logging and controlsystem 120 can elect not to update the reservoir fluid map. In instancesin which an initial reservoir fluid map is not available, the surfacelogging and control system 120 may determine at block 421 to generate areservoir fluid map when a sufficient amount of data has been collectedby the BHA 116.

If the surface logging and control system 120 determines that it shouldupdate the reservoir fluid map data, corrections can be made to thereservoir fluid map stored in the reservoir fluid map database 316. Inthe illustrated example, the fluid simulator 312 (FIG. 3A) determines anew fluid EoS model using the downhole fluid composition analysis datagenerated by the mud gas logging tool 138 and/or the downhole fluidcomposition analysis data generated by the sidewall sampling tool 142(block 422). Example methods that can be used to determine the new fluidEoS model are described in U.S. Patent Application Publ. No.2007/0119244, which is hereby incorporated herein by reference in itsentirety.

Significant differences between the measured composition of the fluidand the fluid composition indicated by the fluid map (determined forexample at block 420) can be indicative of erroneous predicted data(e.g., a horizontal composition gradient has been omitted from the dataused to determine the predicted measurements) and/or one or moreconditions in a reservoir. In the illustrated example of FIGS. 4A and4B, the differences may be indicative of an inaccurate charging model(e.g., the charging model data 334 of FIG. 3B) for the reservoir R and,thus, the charging adjustment interface 336 determines a charging modelfor the reservoir R (block 424) by, for example, fitting a methane orcarbon dioxide charging model to the measurements collected by the mudgas logging tool 138. Additionally or alternatively, the differences maybe indicative of an inaccurate temperature charging model in thereservoir R, and the charging adjustment interface 336 can fit a newtemperature model to the temperature data points collected by thesampling while drilling tool 142 along the drilled well trajectory.

Another reason for the differences may be that an inaccurate fluidconnectivity model 332 was used for determining the reservoir fluid mapof the reservoir R stored in the reservoir fluid map database 316. Theinaccuracy may be detected from pH measurements in contiguous aquifers,or observed deviations of hydrocarbon compositions from compositiongradients predicted using thermodynamic equilibrium (or an appropriateflux model if thermodynamic equilibrium is not indicated). In case suchan inaccuracy is detected, the barrier adjustment interface 338 canupdate the geological model data in the reservoir geological modeldatabase 302 to reflect possible barriers to flow that cannot bedetected with petrophysical logs, geologic logs, or seismic surveys. Thefluid connectivity model 332 may be iteratively altered or adjusteduntil the differences between the measured composition of the fluid andthe fluid composition indicated by the fluid map are within theuncertainty of the measurements. The iterative adjustment may requiremodifying seal or fault positions or transmissibilities, which may beinferred from pressure data, LWD data such as resistivity imaging data,acoustic imaging data, pressure testing data and the like.

When the measured data matches the predicted data along the well 102,the reservoir simulator 314 determines a new reservoir fluid map (block426) by populating the fluid composition properties measured at the wellover the reservoir R and the fluid composition uncertainty map in thereservoir fluid map database 316. In some cases, it may be found thatambiguities or discrepancies in the reservoir architecture need to beresolved to obtain a reservoir fluid map.

The example apparatus 300 then determines whether it should adjust thewell trajectory (block 428). For example, if the updated reservoir fluidmap in the reservoir fluid map database 316 is significantly differentfrom the reservoir fluid map used to plan the well, if an ambiguity oranomaly is detected in the reservoir architecture, or if a measuredfluid property differs substantially from its predicted value, anoperator may elect to adjust the well trajectory, as further describedin connection with FIGS. 5, 6, 7, 8, and 9.

If an adjustment to the well trajectory is considered to be warranted(block 428), the new well trajectory may be determined by simulating oneor more new well trajectory(ies) (block 430) and comparing the merit ofone or more new well trajectory(ies) (block 432) to the current welltrajectory in the well trajectory database 306. For example, thedisplay/input interface 148 can display the one or more new welltrajectories in association with a current well trajectory to enable anoperator to select one of the new well trajectories. The operations ofblocks 430 and 432 may be repeated in an iterative fashion byiteratively simulating new well trajectories and comparing each to thecurrent well trajectory until one of the new simulated well trajectoriesis selected (block 434) by, for example, an operator. In some exampleimplementations, the well production simulator 318 (FIG. 3A) is used toimplement the operations of blocks 430, 432, and 434 to select a welltrajectory to optimize the reservoir drainage/production to, forexample, produce the most economical value. For example, the wellproduction simulator 318 can simulate the drainage/productioncorresponding to various well trajectories, and an operator can selectthe trajectory leading to the most economical value. Alternatively, thetool response simulator 320 (FIG. 3A) can be used to simulate wellsbased on predicted fluid properties (e.g., fluid composition), and awell trajectory can be selected by, for example, an operator based on adesired (or target) measured fluid property corresponding to thepredicted fluid properties. The desired (or target) measured fluidproperties may be associated with steering the well to follow fluidtransition features or to avoid or stay away from other features (e.g.,fluid contacts or tar mats).

After a well trajectory is selected (block 434), the display/inputinterface 148 (FIGS. 1B, 3A, and 3B) updates the well trajectory in thewell trajectory database 306 (block 436), and the surface logging andcontrol system 120 (FIG. 1B) communicates drilling direction commands tothe directional drilling system 118 (FIGS. 1B and 3A) (block 438) toadjust the trajectory of the well 102 (FIG. 1B).

The example apparatus 300 then determines whether the drilling operationis finished (block 440). For example, the drilling operation may befinished if the well 102 is completed and drilling has reached a desired(or target) goal or objective (e.g., a desired drainage/production).Alternatively, the drilling operations may be finished if it isdetermined that no trajectory simulated by the well production simulator318 or the tool response simulator 320 (FIG. 3A) achieves a desiredgoal, in which case drilling operations can be halted on a currentlydrilled well and another well may be started to try and achieve thedesired goal.

If drilling operations have not finished (block 440), the BHA 116continues drilling according to the selected well trajectory (block 442)stored in the well trajectory database 306, and control returns to block412 of FIG. 4A. However, if drilling operations have finished (block440), the surface logging and control system 120 instructs the platformand derrick assembly 100 to retrieve the drill string 104 (block 444)and, thus, the BHA 116. The surface logging and control system 120and/or the computer 146 can generate an operation report (block 446) anddetermine a well trajectory for a subsequent well (block 448). Theexample process of FIGS. 4A and 4B is then ended.

Although the example method of FIGS. 4A and 4B is described as beingperformed in real time while the BHA 116 is in the well and the well 102is being drilled, in other example implementations, the example methodcan be performed in near real time. That is, the data collected duringthe drilling of the well 102 can be analyzed once the BHA 116 is broughtto surface. In such example implementations, a reservoir fluid map canbe created and/or updated as part of an operation report after the well102 has been drilled. The operation report may also include laboratoryanalysis data of the samples drawn while drilling and a comparison ofthe laboratory analysis data and the real time in-situ measurement data.In some example implementations, the trajectory of the next well to bedrilled in the reservoir R can be determined based on the reservoirfluid map as described above in connection with blocks 402, 404, and 406of FIG. 4A.

Although not shown, other reservoir information may also be updatedwhile performing the example method of FIGS. 4A and 4B to, for example,generate the operation report at block 446. For example, the updateddata can include a reservoir fluid pressure map, a geology/lithologymap, and a structural (fault, flow barriers) map. To update this data,other LWD deep measurements (e.g., deep azimuthal resistivitymeasurements, acoustic imaging measurements, formation testing whiledrilling measurements, etc.) could be performed by the BHA 116 and theresults may be used to update the maps.

FIGS. 5, 6, 7, 8, and 9 are flowcharts of example methods that may beused to adjust well trajectories to achieve particular desired (ortarget) results associated with well drainage/production and/or to avoidor target particular structural features in a reservoir. The examplemethods of FIGS. 5, 6, 7, 8, and 9 may be implemented in combinationwith FIGS. 4A and 4B. For example, the example methods of FIGS. 5, 6, 7,8, and 9 may be implemented as variations of the example method of FIGS.4A and 4B to implement respective processes. The example methods ofFIGS. 5, 6, 7, 8, and 9 may be implemented using software and/orhardware. Although the example methods are described with reference tothe flowcharts of FIGS. 5, 6, 7, 8, and 9, the order of execution of theblocks depicted in the flowchart of FIGS. 5, 6, 7, 8, and 9 may bechanged, and/or some of the blocks described may be rearranged,eliminated, or combined to achieve the same or similar results.

Turning to FIG. 5, an example method to determine whether to stopdrilling operations based on real-time well production simulationsinvolves predicting or estimating the production that can be achievedfrom an additional wellbore length yet to be drilled in a well (e.g.,the well 102 of FIG. 1B). At some point during a drilling process theestimated production data for a subsequent wellbore length to be drilledmay indicate a lower economical value (e.g., a low production, aproduction incompatible with the planned surface facility, etc.) thanthe cost of drilling the additional length. Thus, the drilling processcan be stopped.

As shown in FIG. 5, initially one or more initial wellbore length(s) aredrilled (block 502). The sampling while drilling tool 142 (FIGS. 1B-3B)draws a formation fluid sample (block 504) and analyzes the fluid sample(block 506). For example, the sampling while drilling tool 142 can drawthe formation fluid sample via the probe 144 and analyze the fluidsample using the spectrometer 204 and/or the one or more additionalsensor(s) 205 (FIG. 2). Alternatively, the mud gas logging tool 138 isused to capture a portion of the formation fluid present in the drillingfluid 126 once the formation rock has been crushed (block 504) andanalyses a flashed portion of the formation fluid (block 506).Preferably, but not necessarily, the sampling while drilling tool 142and/or the mud gas logging tool 138 measures one or more of formationmobility, GOR, fluid composition, density, viscosity, pressure, andtemperature.

The reservoir simulator 314 updates the reservoir fluid map data storedin the reservoir fluid map database 316 of FIG. 3A (block 508). In someexample implementations, the reservoir simulator 314 adjusts thebiodegradation gradient simulated for the reservoir R to match the fluidsample measurements. In other example implementations, the reservoirsimulator 314 adjusts the thermal gradient simulated for the reservoir Rto match the fluid sample measurement. In yet other exampleimplementations, the fluid sample measurements acquired by the samplingwhile drilling tool 142 or the mud gas logging tool 138 may indicatethat the BHA 116 has entered or is entering a new compartment in thereservoir R containing a different fluid and, thus, the reservoirsimulator 314 adjusts the reservoir fluid map data in the database 316accordingly.

The well production simulator 318 (FIG. 3A) simulates the production ofthe well based on the already drilled wellbore lengths (block 510). Inthe illustrated example, the well production simulator 318 simulates theproduction of the well based on the one or more wellbore lengths drilledat block 502. The well production simulator 318 also simulates theproduction of the well 102 based on the wellbore length to be drilled(block 512). That is, the well production simulator 318 simulates theproduction of the well 102 based on the one or more wellbore lengthsdrilled at block 502 in combination with the wellbore length to bedrilled. In some instances, the well production simulator 318 maysimulate production at block 512 based on a plurality of possiblewellbore lengths that may be drilled, each having a different trajectoryto determine which trajectory of which length will have the mostproduction. In this manner, the well production simulator 318 may selectthe most promising wellbore length and trajectory with which to proceedto the operation of block 516.

The well production simulator 318 then determines the production of thewellbore length to be drilled (block 516). In some instances, the wellproduction simulator 318 may determine that the production from theadded wellbore length to be drilled is small due to, for example, theformation fluid being too viscous, the pressure being too low for thewell to be economically produced, the formation F being of a poorerquality than had been anticipated, and/or elements in the fluid willrapidly precipitate and clog the part of the formation where the well102 is to be drilled. Additionally or alternatively, the well productionsimulator 318 may determine that the production from the added lengthwill result in producing too much gas at the surface and that theproduction facilities which have to be constructed to handle theproduced gas would be prohibitively costly.

The surface logging and control system 120 then determines whether tocontinue drilling (block 518) the additional wellbore length. Forexample, the display/input interface 148 (FIGS. 1B, 3A and 3B) canreceive input from an operator indicating whether to continue or stopdrilling operations. If the surface logging and control system 120determines that drilling should continue (block 518), the surfacelogging and control system 120 instructs the BHA 116 to drill the nextwellbore length, and control is passed back to the operation of block504. Otherwise, the surface logging and control system 120 instructs theBHA 116 (FIG. 1B) to stop drilling operations (block 522), and theplatform and derrick assembly 100 retrieves the drill string 104 (block524). The example process of FIG. 5 is then ended. In some exampleimplementations, the well 120 may be drilled further if, for example,other productive portions of the reservoir R may be reached bycontinuing to drill the well 120 even if the immediately subsequentlength to be drilled is predicted to be uneconomical to produce.

Turning to FIG. 6, the depicted example method can be used to place awell in a reservoir containing injected fluid, such as gas. The examplemethod may be used, for example, in instances in which new wells aredrilled with the intent of recovering bypassed oil in a reservoir thathas been under primary production or has been produced using injection.In the illustrated example, the example method is implemented to followprimary production by injecting gas which is miscible with the oilremaining in the reservoir R with the expectation that the oil recoveryfactor will increase. However, two typical concerns associated with themanagement of gas injection schemes include maintaining the gas pressureabove a minimum miscibility pressure and knowing the position of theinjection front throughout the reservoir R. Using the depicted examplemethod of FIG. 6, the uncertainty in knowing the location of theinjected gas front can be progressively reduced as new wells aredrilled, thus improving the placement of current, sidetrack or futurewells. To further reduce the uncertainty in knowing the location of theinjected gas front, the pressure in the reservoir R may be monitored atvarious locations along newly drilled wells.

As shown in FIG. 6, initially, the reservoir simulator 314 may generatea reservoir fluid saturation map, that is representative of, amongstother things, the distribution of relative proportions of pristineformation fluid and/or injection fluid in the reservoir R (e.g., asaturation level of injected fluid) (block 602). In the illustratedexample, the reservoir simulator 314 may generate at least a gassaturation map and additionally a pressure contour map, both of whichreflect the incremental gas injection history and the oil production atthe producing wells. The tool response simulator 320 generates predictedfluid measurement log data for one or more well(s) to be drilled (block604). Some of the predicted log data may correspond to anticipated fluidsampling log data based on the fluid saturation map generated at block602 at stations where in-situ fluid compositions are to be sampled.Other predicted log data may include a pressure profile along a wellhaving pressures acquired at the same sampling station. Yet otherpredicted log data may correspond to possible gas breakthrough from anearby injection well.

The sampling while drilling tool 142 (FIGS. 1B-3B) draws a formationfluid sample (block 606) and analyzes the fluid sample (block 608). Forexample, the sampling while drilling tool 142 can draw the formationfluid sample via the probe 144 and analyze the fluid sample using thespectrometer 204 and/or the one or more additional sensor(s) 205 todetermine a fluid sample composition, and in particular the relativeproportions of pristine formation fluid and/or injection fluid in thefluid sample. Alternatively, the mud gas logging tool 138 may be used toanalyze the composition formation fluid (e.g., analyze a concentrationratio between methane, or any other injected gas such as carbonedioxide, and another group of hydrocarbons such as embodied in the socalled wetness ratio commonly used in mud gas logging). Preferably, butnot necessarily, the measurements performed by the sampling whiledrilling tool 142 and/or the mud gas logging tool 138 include massspectra measurements, gas chromatography measurements, opticalreflectance measurements, optical absorbance spectra measurements in thenear infrared range (e.g., at wavelengths characteristic of oil, methaneand carbon dioxide), emulsion detection measurements from ultravioletfluorescence, pressure measurements, temperature and fluid densitymeasurements, and/or viscosity and mobility measurements.

A fluid sample composition determined at block 608 is then compared tothe predicted and/or desired (or target) (e.g., sufficiently low) logdata determined at block 604 (block 610). In the illustrated example,the comparison is used along with pressure measurements for a proposedwell to determine if the pressure in the proposed well is sufficient foran injected gas to be miscible with in-situ oil and if the gas injectionscheme is effective in contacting and mobilizing the remaining oil inthe well formation F (FIG. 1B). When the comparison of block 610 isperformed for different points along the proposed well, each comparisonmay indicate a different result such that some portions of the proposedwell have sufficient pressure while others may not. In the illustratedexample, the comparison of block 610 will also indicate what changesshould be made to reservoir fluid map data in the reservoir fluid mapdatabase 316 to reflect the latest data acquired at block 608.

For each one of the well(s) to be drilled, the reservoir simulator 314updates respective formation evaluation logs in the formation evaluationlogs database 304 (block 612) and geological logs in the reservoirgeological model database 302 (block 614). In the illustrated example,the example apparatus 300 also updates the pressure map in the reservoirfluid map database 316 (block 616) and the reservoir fluid saturationmap in the reservoir fluid map database 316 (block 618). The updates ofblocks 612, 614, 616, and 618 facilitate determining a more accuratereservoir fluid saturation map and associated uncertainty map of thereservoir R. In example implementations in which the comparison of block610 indicates no change in the formation evaluation model and thegeological model, the formation evaluation model and the geologicalmodel need not be updated at block 612 and 614.

The example apparatus 300 determines one or more possible wellborelength extension(s) that can be drilled in a current or one or moresubsequent well(s) based on the updated reservoir fluid saturation map(block 620). For example, additional possible lengths may includelengths that steer the well 102 (FIG. 1B) in a different direction orthat continue drilling in the same direction to acquire additionalinformation to make subsequent drilling decisions. For example, theadditional information may be used to better understand the injectiongas front of the reservoir R (FIG. 1B) to plan a next well in thereservoir R. In the illustrated example, the example apparatus 300 (oran operator using the apparatus 300) may determine based on thecomparison of block 610 that no subsequent lengths should be drilled andthat the drilling of a current well should stop when, for example, thewell in its current form may be used as a producer or as a gas injector.

In some example implementations, the operations of block 610 and/or 620could be performed by an operator (e.g., a database update decisionbased on the comparison, a well trajectory selection based on thecomparison, etc.) and the operator could provide user input to theexample apparatus 300, based on a display or presentation configurationor arrangement that facilitates an operator-performed comparison of thedata via the terminal display/input console 148.

Turning to FIG. 7, the depicted example method can be used to adjustwell trajectories to plan a well in a compartmentalized reservoir. Inthe illustrated example of FIG. 7, potential compartmentalization in areservoir is resolved during the drilling of the well, and the welltrajectory can be modified based on an understanding of the fluidheterogeneity in the compartmentalized reservoir. Barriers to fluid flowin a compartmentalized reservoir are typically properties of thegeological structures that contain the fluids. Barriers to fluid flow inrock structures often manifest themselves in measurable changes in fluidproperties; for example, as a discontinuous change in some fluidparameter (e.g., parameters that can be measured using downhole fluidanalysis (DFA) techniques include, a color parameter, a GOR parameter,an asphaltene content parameter, a CO2 content parameter, a gascomposition parameter, a density parameter, a viscosity parameter, a pHparameter and a salinity parameter). In addition, flow barriers oftenmanifest themselves by having higher density fluid in the oil column atlocations which would violate static equilibrium. In the illustratedexample described below, predicted data from a current geologic model isused to find flow barriers (e.g., flow barrier 180 of FIG. 1B). Inaddition, the example method of FIG. 7 can be used to detect barriers orpossible barriers based on measurement data acquired using other toolssuch as, for example, the PeriScope™ resistivity tool developed and soldby Schlumberger Technology Corporation. The example method of FIG. 7 canbe implemented using several DFA stations, each positioned on adifferent side of a potential barrier to detect fluid manifestations ofbarriers.

As shown in FIG. 7, initially the tool response simulator 320 generatespredicted fluid measurement log data for a well (block 702). In theillustrated example, the predicted log data corresponds to fluidcomposition and/or fluid properties such as, for example, mass densityand viscosity, typically in a sand shale sequence along a firsttrajectory. The sampling while drilling tool 142 (FIGS. 1B-3B) draws aformation fluid sample (block 704) and analyzes the fluid sample (block706). For example, the sampling while drilling tool 142 can draw theformation fluid sample via the probe 144 and analyze the fluid sampleusing the spectrometer 204 and/or the one or more additional sensor(s)205. Preferably, but not necessarily, the measurements acquired usingthe sampling while drilling tool 142 include fluid density and viscositymeasurements, mass spectra measurements, gas chromatographymeasurements, and/or optical absorbance spectra measurements. At block706 the sampling while drilling tool 142 and/or the surface logging andcontrol system 120 (FIG. 1B) can use the mass spectra, gaschromatography, and/or optical absorbance spectra measurements todetermine, at least, the proportions of C1, C2, C3-5, C6+, CO2, H2O,and, in the case of optical absorbance, color, which can be used todetermine the GOR and various ratios of combinations of the hydrocarboncomponents in the fluid sample.

The fluid sample measurements (and/or fluid composition) determined atblock 706 are compared to the predicted log data determined at block 702(block 708). In addition, fluid compartmentalization is resolved (block710) and the existence and locations of flow barriers (e.g., flowbarrier 180 of FIG. 1B) in the reservoir are identified (block 712)based on the fluid compartmentalization. The operations of blocks 708,710, and 712 can be performed by an operator observing the differentdata and/or comparisons thereof via the display/input interface 148(FIGS. 1B, 3A, and 3B). In other example implementations, the operationsof blocks 708, 710, and 712 can be implemented using software and/orhardware configured to perform such analyses.

The example apparatus 300 then adjusts the well trajectory (block 710)based on flow barriers identified at block 712 (block 714). For example,if a fluid composition or fluid property falls outside the predictedrange determined at block 702, a well trajectory may be adjusted tointersect a separate sand shale sequence to check the fluid containedtherein. In some example implementations, different well trajectoriescontingent on fluid findings can be developed prior to beginningdrilling operations of a well. The example process of FIG. 7 is thenended. Although not shown, the process of FIG. 7 can be repeated until awell is completely drilled or until a determination is made thatdrilling operations should no longer continue for the well.

In some example implementations using the example method of FIG. 7,other thermodynamic models based on first principles can be used tomodel the variations in concentration of asphaltenes and resins in afluid. Asphaltenes and resins are the heaviest components of crude oil.Hydrocarbons could have minimal concentration variations of relativelylighter components and yet have an identifiable concentration variationof asphaltenes and or resins. Asphaltenes and resins dictate orinfluence the color of crude oil and can be measured in-situ by DFAtechniques. Preferably, but not necessarily, under sampling conditionsin which a fluid is pristine and no phase transitions have occurred, DFAmeasurement techniques can be used to achieve relatively more accuratemeasurement data of asphaltene-resin concentrations in a fluid.Variations in asphaltene and resin concentrations can be indicators ofreservoir compartments. The large molecular aggregates of asphaltenesand resins are subject to buoyancy forces and, thus, anomalous changesin the natural distribution of these components within reservoirs aretypically indicative of flow barriers.

Turning to FIG. 8, the depicted example method can be used to steer awell based on asphaltene precipitation onset pressure. In theillustrated example, the example method can be used to produce wellshaving relatively fewer flow assurance problems than might be achievedusing other, traditional drilling techniques. The example method of FIG.8 uses characteristics such as, for example, fluid compositionsrepresented by a reservoir fluid map to generate an asphalteneprecipitation onset pressure map. In this manner, a well trajectory canbe steered based on the precipitation onset pressure map.

As shown in FIG. 8, initially, the sampling while drilling tool 142(FIGS. 1B-3B) draws a formation fluid sample (block 802) and analyzesthe fluid sample (block 804). For example, the sampling while drillingtool 142 can draw the formation fluid sample via the probe 144 andanalyze the fluid sample using the spectrometer 204 and/or the one ormore additional sensor(s) 205. Preferably, but not necessarily, themeasurements acquired using the sampling while drilling tool 142 includemeasures of optical absorption in the visible range and pressuremeasurements. Asphaltene typically causes an optical absorption thatvaries in the visible light range exponentially with the lightfrequency. Typically, asphaltene concentrations can be determined whengravity segregation and chemical equilibrium in the reservoir R areacting to generate or influence the presence of such asphalteneconcentrations. At block 804, the sampling while drilling tool 142and/or the surface logging and control system 120 (FIG. 1B) correlatethe color of the formation fluid to an asphaltene concentration in thefluid to refine the asphaltene concentration measure based on theformation fluid color.

The reservoir simulator 314 then generates a reservoir fluid map (block806) based on the asphaltene concentration. The reservoir fluid map canbe determined by modeling how gravity segregation and chemicalequilibrium affects variations in the concentrations of asphaltene atdifferent subsurface depths. The fluid simulator 312 (FIG. 3A) generatesa precipitation onset pressure map (block 808) based on the reservoirfluid map generated at block 806. In the illustrated example, the fluidsimulator 312 generates the precipitation onset pressure map using anEoS equation.

The example apparatus 300 (or an operator) then compares theprecipitation onset pressure map with production pressure in the well(block 810). For example, the precipitation onset pressure map generatedat block 808 can be compared to production pressures predicted by thewell production simulator 318 and pressure measurements acquired atblock 804. In some example implementations, the comparison operation ofblock 810 could be performed by an operator (e.g., an operator-performedcomparison) and the operator could provide user input based on thecomparison (e.g., a well trajectory selection based on the comparison,etc.). For example, the computer 146 (FIG. 1B) could receive theprecipitation onset pressure map from the fluid simulator 312 andproduction pressures from the well production simulator 318 and displaythe at least a portion of precipitation onset pressure map andproduction pressures via the terminal display/input console 148 using adisplay or presentation configuration or arrangement that facilitates anoperator-performed comparison of the data.

The example apparatus 300 then adjusts the well trajectory based on thecomparison (block 812). For example, the direction of drilling may beadjusted to avoid zones in the reservoir R that have a precipitationpressure that is too low. Thus, the well trajectory adjustment of block812 may be made based on the comparison at block 810 and a comparison ofmeasured and predicted fluid properties that are computed from a fluidcomposition (e.g., precipitation onset pressure, equation of state(EoS), etc.).

For example, if a measured fluid composition indicates a precipitationonset pressure that is significantly different from a desired (ortarget) value, the well trajectory may be adjusted at block 812 to avoidzones in the reservoir R that have a precipitation pressure that is toolow and/or to achieve a well trajectory that will produce a desired (ortarget) fluid precipitation pressure along the drilled well. In somecases, drilling of a well may be stopped when it is determined thatsubsequent drilling will not achieve a desired (or target) or necessaryprecipitation pressure.

The example apparatus 300 then determines whether the BHA 116 (FIG. 1B)should continue drilling a current well (block 814). For example, theexample apparatus 300 may determine based on the comparison of block 810that the drilling of the current well should be stopped if subsequentdrilling will not achieve a desired or necessary precipitation pressure.Otherwise, if a well trajectory is selected at block 812 that can avoidzones in the reservoir R that have a precipitation pressure that is toolow, drilling may continue. If drilling is to continue, control ispassed back to block 802. Otherwise, control passes to block 816, andthe example apparatus 300 is used to determine a well trajectory for anext well (block 816). In the illustrated example, a well trajectory fora side track well to be drilled in the same reservoir R may bedetermined based on the precipitation onset pressure map. The exampleprocess of FIG. 8 is then ended.

Turning to FIG. 9, the depicted example method can be used to controlthe trajectory of a well (e.g., an almost horizontal well) to maintainthe well trajectory below a gas-oil contact in an oil zone. The examplemethod of FIG. 9 can be advantageously used to determine relativelybetter well trajectories relative to gas-oil contacts than can beachieved using resistivity tools because gas-oil contacts do not offer aresistivity contrast. Also, in the case of light hydrocarbons having atransition to rich condensate gas, little or relatively low acousticalcontrast between the oil zone and the gas zone exists. However, theexample method of FIG. 9 can be advantageously used to determinerelatively better well trajectories relative to gas-oil contacts thancan be achieved using acoustic tools. Where relatively large gradientsin fluid properties exist, the example method of FIG. 9 can beadvantageously used to determine the gas-oil contact and adjust a welltrajectory based on that gas-oil contact.

As shown in FIG. 9, initially, the sampling while drilling tool 142(FIGS. 1B-3B) draws a formation fluid sample (block 902) and analyzesthe fluid sample (block 904). For example, the sampling while drillingtool 142 can draw the formation fluid sample via the probe 144 andanalyze the fluid sample using the spectrometer 204 and/or the one ormore additional sensor(s) 205. Preferably, but not necessarily, themeasurements acquired using the sampling while drilling tool 142 includeGOR, C1, C2, C3-C5, and C6+ concentrations, and saturation pressure,i.e. bubble point/dew point pressure, measurements at reservoirtemperature. Alternatively or additionally the mud gas logging tool 138may be used to acquire composition data of the reservoir fluid.

The reservoir simulator 314 then generates a reservoir fluid map (block906) based on the measurements acquired at block 904, including fluidcomposition and/or saturation pressure predictions. In the illustratedexample, to generate the reservoir fluid map, the fluid simulator 312assumes that a chemical equilibrium exists in the reservoir R. The fluidsimulator 312 also determines or identifies the existence of a gas-oil(or water-oil) contact in the fluid map generated at block 906 (block908).

The example apparatus 300 then adjusts a well trajectory based on thedetermined contact (block 910). For example, the example apparatus 300may adjust the well trajectory to maintain the well in an oil zone at adesired (or target) distance from the gas-oil contact determined atblock 908. The well trajectory may be adjusted at block 910 based on thecontact identified at block 908 by comparing a measured fluid property(e.g., a fluid composition and/or a saturation pressure) and a fluidproperty predicted in the fluid map. The point of the fluid map at whichthe measured and predicted properties match indicates a distance from agas-oil contact. If the indicated distance is significantly differentfrom a desired (or target) distance, the well trajectory may be adjustedto achieve a desired distance. The example process of FIG. 9 is thenended. Although not shown, the process of FIG. 9 can be repeated until awell is completely drilled or until a determination is made thatdrilling operations should no longer continue for the well.

In some example implementations, the comparison operation of block 910could be performed by an operator (e.g., an operator-performedcomparison) and the operator could provide user input based on thecomparison (e.g., a well trajectory selection based on the comparison).For example, the computer 146 (FIG. 1B) could receive fluid properties(e.g., a fluid composition and/or a saturation pressure) measured alongthe well trajectory from the BHA 116 and display the received fluidproperties on the reservoir fluid map via the terminal display/inputconsole 148 using a presentation configuration or arrangement thatfacilitates an operator-performed comparison of the BHA 116 location andgas-oil contact location.

In some example implementations, the example methods of FIG. 9 can alsobe used to adjust or steer well trajectories relative to an oil-watercontact or to maintain a position relative to biomarkers or the qualityof an oil body where the quality is, for example, a measure of thedegree of biodegradation that has taken place. In such exampleimplementations, measurements acquired using the sampling while drillingtool 142 at block 904 include measurements of benzene and toluene in thecase of the oil-water contacts, fluid composition measurements up to atleast C30 in the case of biodegradation, and/or carbon and hydrogenisotopic ratio measurements. To determine fluid compositions based onbiodegradation, the sampling while drilling tool 142 can alternativelybe used to measure in-situ density, GOR, gas gravity, and viscosity, andthe degree of biodegradation may be inferred from local correlations ofsuch measurements.

In view of all of the above and the figures, those skilled in the artshould readily recognize that the present disclosure introduces a methodcomprising acquiring mud gas logging data, comparing the mud gas loggingdata to second data associated with a sidewall fluid sample measurement,and adjusting calibration data associated with a mud gas logging toolbased on the comparison of the mud gas logging data and the second dataassociated with the sidewall fluid sample measurement. The method mayfurther comprise performing the comparison of the mud gas logging datato the second data when the mud gas logging data indicates a change in afluid composition. The second data may be one of a fluid composition ora concentration of a fluid component.

The present disclosure also introduces a method comprising acquiring mudgas logging data, comparing the mud gas logging data to one of apredetermined fluid composition or a predetermined concentration of afluid component, and initiating a sidewall fluid sample measurementbased on the comparison. Such method may further comprise acquiringsecond data associated with a sidewall fluid sample measurement. Suchmethod may further comprise comparing the mud gas logging data to thesecond data, and adjusting calibration data associated with a mud gaslogging tool based on the comparison of the mud gas logging data and thesecond data.

The present disclosure also introduces an apparatus comprising a mud gaslogging tool configured to acquire mud gas logging data and comprising afirst sensor operatively coupled to a tool inlet for admitting fluidcontained in a well. The apparatus further comprises a sidewall fluidsampling tool operatively coupled to the mud gas logging tool andcomprising a second sensor configured to selectively couple to aformation penetrated by the well to acquire sidewall fluid samplemeasurements. The apparatus may further comprise a directional drillingassembly configured to adjust a well trajectory based on at least one ofmud gas logging data and sidewall fluid sample measurements. Theapparatus may further comprise a probe configured to form a fluidcommunication with the formation penetrated by the well.

The present disclosure also introduces a method comprising determining areservoir fluid property map on a portion of a reservoir, conveying afluid property sensor into a reservoir well, using the sensor to performin-situ measurements indicative of a formation fluid property, comparingthe in-situ measurements with the property map, and adjust a welltrajectory based on the comparison. Such method may further comprisingdetermining a reservoir fluid property uncertainty map on at least thesame portion of the reservoir, determining the uncertainty associatedwith the in-situ measurements performed by the sensor, and comparing thein-situ measurement uncertainties with at least one of the property mapand its associated uncertainty map. Conveying the fluid property sensorinto the reservoir well may use at least one of a drill string and awireline.

The foregoing outlines features of several embodiments so that thoseskilled in the art may better understand the aspects of the presentdisclosure. Those skilled in the art should appreciate that they mayreadily use the present disclosure as a basis for designing or modifyingother processes and structures for carrying out the same purposes and/orachieving the same advantages of the embodiments introduced herein.Those skilled in the art should also realize that such equivalentconstructions do not depart from the spirit and scope of the presentdisclosure, and that they may make various changes, substitutions andalterations herein without departing from the spirit and scope of thepresent disclosure.

What is claimed is:
 1. A method, comprising: determining a reservoirfluid property map on a portion of a subterranean hydrocarbon reservoir;conveying a fluid property sensor into a well penetrating the reservoir;using the sensor to perform in-situ measurements indicative of a fluidproperty of reservoir fluid in the reservoir; comparing the in-situmeasurements with the reservoir fluid property map; and adjusting atrajectory of the well based on the comparison.
 2. The method of claim 1further comprising: determining a reservoir fluid property uncertaintymap on at least the portion of the reservoir; determining uncertaintiesassociated with the in-situ measurements; and comparing theuncertainties with at least one of the reservoir fluid property map andthe reservoir fluid property uncertainty map.
 3. The method of claim 1wherein conveying the fluid property sensor into the well uses at leastone of a drill string and a wireline.
 4. The method of claim 1 whereinthe reservoir fluid property map comprises a map of a property relatedto composition of the reservoir fluid.
 5. The method of claim 4 whereinusing the sensor to perform in-situ measurements comprises using thesensor to perform in-situ measurements of the property.
 6. The method ofclaim 1 wherein the reservoir fluid property map comprises a map of atleast one compositional component of the reservoir fluid.
 7. The methodof claim 6 wherein using the sensor to perform in-situ measurementscomprises using the sensor to perform in-situ measurements of the atleast one compositional component.
 8. The method of claim 1 wherein thereservoir fluid property map comprises a map of constituent isotoperatios within the reservoir.
 9. The method of claim 1 wherein thereservoir fluid property map comprises a map of gas-liquid ratios withinthe reservoir.
 10. The method of claim 1 wherein the reservoir fluidproperty map comprises a map of thermo-physical data within thereservoir.
 11. The method of claim 10 wherein the thermo-physical datais selected from the group consisting of: fluid bulk density; saturationpressure; viscosity; fluid acoustic impedance; and fluidcompressibility.
 12. The method of claim 11 wherein adjusting thetrajectory comprises adjusting a parameter of the trajectory selectedfrom the group consisting of direction, travel, and path.
 13. The methodof claim 11 wherein adjusting the trajectory comprises terminatingplanned drilling operations.
 14. A method, comprising: conveying a fluidproperty sensor into a well penetrating a subterranean hydrocarbonreservoir; using the sensor to perform in-situ measurements indicativeof a fluid property of reservoir fluid in the reservoir; determining areservoir fluid property map for at least a portion of the reservoirbased on the in-situ measurements; and adjusting a well trajectory basedon the reservoir fluid property map.
 15. The method of claim 14 furthercomprising determining a reservoir fluid property uncertainty mapassociated with the in-situ measurements.
 16. The method of claim 15wherein adjusting the well trajectory based on the reservoir fluidproperty map comprises adjusting the well trajectory based on at leastone of the reservoir fluid property map and the reservoir fluid propertyuncertainty map.
 17. The method of claim 15 wherein adjusting the welltrajectory based on the reservoir fluid property map comprises adjustingthe well trajectory based on the reservoir fluid property map and thereservoir fluid property uncertainty map.
 18. A method, comprising:determining a reservoir fluid property map on a portion of asubterranean hydrocarbon reservoir; extending a well relative to thereservoir using a drill string comprising a drill bit and bottom-holeassembly (BHA) comprising a mud gas logging tool, including obtainingmud gas logging data using the mud gas logging tool while extending thewell via rotation of the drill bit; comparing the mud gas logging datawith the reservoir fluid property map; and adjusting a trajectory of thewell based on the comparison.
 19. The method of claim 18 furthercomprising: pausing rotation of the drill bit at least long enough toobtain a sample of the reservoir fluid through a sidewall of the wellusing a sidewall sampling tool of the BHA; obtaining measurement datafrom the sample; comparing the measurement data to the mud gas loggingdata; adjusting a calibration associated with the mud gas logging tool;further extending the well relative to the reservoir by resumingrotation of the drill bit.
 20. The method of claim 18 wherein adjustingthe trajectory comprises: simulating a new trajectory; comparing the newtrajectory with the current trajectory; and selecting the new trajectorybased on the comparison.